NHS Digital Data Release Register - reformatted

NHS Wakefield CCG

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

Project 1 — NIC-90713-T3K1V

Opt outs honoured: N, Y

Sensitive: Sensitive

When: 2017/03 — 2018/05.

Repeats: Ongoing

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

Categories: Anonymised - ICO code compliant, Identifiable

Datasets:

  • Children and Young People's Health Services Data Set
  • Improving Access to Psychological Therapies Data Set
  • Local Provider Data - Acute
  • Local Provider Data - Ambulance
  • Local Provider Data - Community
  • Local Provider Data - Demand for Service
  • Local Provider Data - Diagnostic Services
  • Local Provider Data - Emergency Care
  • Local Provider Data - Experience Quality and Outcomes
  • Local Provider Data - Public Health & Screening services
  • Local Provider Data - Mental Health
  • Local Provider Data - Other not elsewhere classified
  • Local Provider Data - Population Data
  • Local Provider Data - Primary Care
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • Maternity Services Dataset
  • SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  • SUS for Commissioners
  • Public Health and Screening Services-Local Provider Flows
  • Primary Care Services-Local Provider Flows
  • Population Data-Local Provider Flows
  • Other Not Elsewhere Classified (NEC)-Local Provider Flows
  • Mental Health-Local Provider Flows
  • Maternity Services Data Set
  • Experience, Quality and Outcomes-Local Provider Flows
  • Emergency Care-Local Provider Flows
  • Diagnostic Services-Local Provider Flows
  • Diagnostic Imaging Dataset
  • Demand for Service-Local Provider Flows
  • Community-Local Provider Flows
  • Children and Young People Health
  • Ambulance-Local Provider Flows
  • Acute-Local Provider Flows

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), North of Engalnd CSU receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not. Risk Stratification To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care. Commissioning (Pseudonymised) – SUS and Local Flows To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services : - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Diagnostic Imaging Data Set (DIDS) The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.

Expected Benefits:

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

Outputs:

Invoice Validation 1. Addressing poor data quality issues 2. Production of reports for business intelligence 3. Budget reporting 4. Validation of invoices for non-contracted events Risk Stratification 1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. 3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level and aggregate with small number suppression. 4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient. Commissioning (Pseudonymised) – SUS and Local Flows 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals POD. e. Planned care by POD view – activity, finance plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include frequent flyers. 9. Mortality 10. Quality 11. Service utilisation reporting 12. Patient safety indicators 13. Production of reports and dash boards to support service redesign and pathway changes Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include frequent flyers.

Processing:

Invoice Validation Data Processor 1 – North of England CSU SUS Data is obtained from the SUS Repository to DSCRO. 1. DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU. 2. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  3. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Risk Stratification Data Processor 2 – eMBED Identifiable SUS data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO). 1. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to eMBED, who hold the SUS data within eMBED secure storage. 2. Identifiable GP Data is securely sent from the GP system to eMBED. 3. SUS data is linked to GP data in the risk stratification tool by the data processor. 4. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS number of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems. 5. eMBED who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication. 6. Once eMBED has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level. Commissioning (Pseudonymised) – SUS and Local Flows 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 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. No data sourced from another provider will be shared. 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 2 — NIC-60447-S8K9F

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • SUS (Accident & Emergency, Inpatient and Outpatient data)
  • Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Other not elsewhere classified, Population Data, Primary Care, Public Health & Screening services

Objectives:

SUS and Local Provider Data - The CCG recognises that good information and intelligence is crucial for the commissioning of high quality and safe services leading to better outcomes for the populations they serve. This application supports this objective. This arrangement was previously agreed to facilitate the transfer of Commissioning Support Services, from Yorkshire & Humber Commissioning Support Unit (Y&H CSU), who previously held ASH status and served the CCGs, to North England CSU (NECS), and eMBED Health Consortium, for ongoing provision in line with the NHS England Lead Provider Framework (LPF). Data Processor 1 - NECS is a commissioning support unit that had been working with the CCG for some time. Data Processor 2 - eMBED was appointed in March 2016 to continue the operations of the Yorkshire and Humber CSU; Kier Business Services Limited, with additional Business Intelligence work carried out under contract by Dr Foster Ltd. Kier Business Services are the prime partner for the LPF within the eMBED Health Consortium. Both organisations (Kier Business Services and Dr Foster Ltd) are a legal entity in their own right. Dr Foster Ltd are subcontracted to Kier Business Services for the delivery of eMBED Health Consortium services.

Expected Benefits:

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

Outputs:

1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers. 9. Monitoring of hospital activity against planned levels where an established contract exists between a provider and a commissioner inclusive of: o Overall contract reporting of actual vs plan for activity and value at aggregate level o Reconciliation reports between local hospital data, and SUS records at aggregate level. o Contract Data Quality reporting at anonymised in context record level. 10. QIPP scheme analysis at aggregate level 11. Monitoring of SUS based CCG Outcome Framework indicators at aggregate level with small number suppression. 12. “Deep dive” analysis of hospital activity at aggregate level. 13. Cross CCG benchmarking at aggregate level. 14. Provision of aggregate reports with small number suppression activity data to CCGs’ stakeholders e.g. Health and Wellbeing Boards where the CCG have agreed to this

Processing:

1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North England DSCRO also obtains identifiable local provider data for the CCG directly from Providers. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis. 3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG. 4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning: - SUS data and Local Provider data at pseudonymised level - Mental Health (MHSDS, MHLDDS, MHMDS) with SUS - Improving Access to Psychological Therapies (IAPT) with SUS - Diagnostic Imaging Dataset (DIDs) with SUS - Maternity (MSDS) with SUS - Children and Young People’s Health Services (CYPHS) with Local provider data - Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data - Improving Access to Psychological Therapies (IAPT) with Local provider data - Diagnostic Imaging Dataset (DIDs) with Local provider data - Maternity (MSDS) with Local provider data - Children and Young People’s Health Services (CYPHS) with Local provider data 5. eMBED securely transfer pseudonymised outputs for management use by the CCG. 6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 7. Aggregation of required data for CCG management use will be completed by the CSU, eMBED or the CCG as instructed by the CCG. 8. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place. 9. The CCG securely transfer Pseudonymised data back to the provider to: a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery; b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider.


Project 3 — NIC-56452-T0G7M

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • SUS (Accident & Emergency, Inpatient and Outpatient data)

Objectives:

As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by the CSU whether payment for invoices can be made or not. No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

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

Outputs:

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

Processing:

North of England DSCRO (part of NHS Digital) will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO. 1. SUS Data is obtained from the SUS Repository to North of England DSCRO. 2. North of England DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU. 3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.


Project 4 — NIC-22542-R0Q7P

Opt outs honoured: Y

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

  • SUS (Accident & Emergency, Inpatient and Outpatient data)

Objectives:

To utilise SUS data Identifiable at the level of NHS number to provide risk stratification information to the GP practice.

Expected Benefits:

To provide risk profiling, calculated on activity data from secondary and primary care. As part of the risk stratification processing activity detailed above, the GP have access to the eMBED CPM web-tool for reports which presents to them their registered patients and associated risk score. The GP can access the eMBED CPM web-tool which is a secure portal at any time which will support multi-disciplinary team discussions around ongoing patient care, enhanced service requirements and supporting patient care. The GP can copy and paste the NHS number presented in the eMBED CPM web-tool to any other program including the practice clinical system, in order to perform the key aspects of this risk stratification role. There are two outputs available in the eMBED CPM web-tool, these are: • Identifiable Reports – containing a record for each patient with NHS number, name and unique identifier Patient ID which is added to each record during data processing. Non-Identifiable Reports – NHS number and name are removed but the record still contains the unique identifier patient ID. The GP practice authorises the access to the eMBED CPM web-tool, the level of access and which view is available. Aggregated outputs are available to the CCG on request via eMBED. No data will be shared with any other third party organisations.

Outputs:

To provide risk profiling, calculated on activity data from secondary and primary care. As part of the risk stratification processing activity detailed above, the GP have access to the eMBED CPM web-tool for reports which presents to them their registered patients and associated risk score. The GP can access the eMBED CPM web-tool which is a secure portal at any time which will support multi-disciplinary team discussions around ongoing patient care, enhanced service requirements and supporting patient care. The GP can copy and paste the NHS number presented in the eMBED CPM web-tool to any other program including the practice clinical system, in order to perform the key aspects of this risk stratification role. There are two outputs available in the eMBED CPM web-tool, these are: • Identifiable Reports – containing a record for each patient with NHS number, name and unique identifier Patient ID which is added to each record during data processing. Non-Identifiable Reports – NHS number and name are removed but the record still contains the unique identifier patient ID. The GP practice authorises the access to the eMBED CPM web-tool, the level of access and which view is available. Aggregated outputs are available to the CCG on request via eMBED. No data will be shared with any other third party organisations.

Processing:

Processing of SUS Data for the purposes of Risk Stratification includes landing, processing, staging and publication. 1. Landing Prior to the release of SUS data by DSCRO Yorkshire, Type 2 objections will be applied and the relevant patients data redacted. DSCRO Yorkshire securely transfer the SUS data identifiable at the level of NHS number. Data is landed and processed in an access restricted data centre located at eMBED. Only named individuals have access to process the data. All users undertake regular IG training, in line with IGT & ISO 27001:2013 requirements. 2. Processing Data is processed on a monthly basis. 2.1. Data is extracted from primary care systems and downloaded to a secure storage area within eMBED, it is then processed to exclude data for patient objections and sensitive conditions 2.2. Cleaning and quality checks are carried out and documented. 2.3. SUS and primary care data are linked. 2.4. Creation of Risk Stratification dataset. 2.5. Risk Stratification dataset processed through CPM Risk Stratification Algorithm to produce a Risk Stratified scoring dataset. 3. Staging Data is landed to a secure staging area for final quality checks before forwarding to the live server. 4. Publication Outputs are available to GP practice for their own patients only via the eMBED CPM web-portal. Access to the eMBED CPM web-portal is via username and password. All usage of its tools is audited this is controlled by the practices. There are two outputs available, these are: • Identifiable Reports – containing a record for each patient with NHS number, name and unique identifier Patient ID which is added to each record during data processing. • Non-Identifiable Reports – NHS number and name are removed but the record still contains the unique identifier patient ID. (The Patient ID is generated during the loading and processing and are used in referencing the different tables so no one knows these numbers.) Data identifiable at the level of NHS number is only available to named individuals within the GP Practices who have a legitimate relationship with the patient. The web-portal is accessed by the GP using a username and password. The GP have direct access to any underlying patient level SUS data where they can see all aspects of the inpatient and outpatient activity. The GP also has access to the diagnosis data from both SUS data and the primary care data.


Project 5 — NIC-21957-H4T8B

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • Mental Health Minimum Data Set
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Services Data Set
  • Improving Access to Psychological Therapies Data Set
  • Children and Young People's Health Services Data Set

Objectives:

To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services: • Mental Health Minimum Data Set (MHMDS) • Mental Health Learning Disability Data Set (MHLDDS) • Mental Health Services Data Set (MHSDS) • Improving Access to Psychological Therapy (IAPT) • Children and Young People’s Health (CYPHS) The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.

Expected Benefits:

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

Outputs:

As a result of the aforementioned processing activities, eMBED will provide a number of outputs which are securely provided to the CCGs in the appropriate format at pseudonymised level. Where datasets have been linked, the CCG will receive the outputs of analysis instead of the direct data, however it may also be necessary to provide linked data at row level to CCGs (pseudonymised record level data). eMBED will provide aggregated reports only with small number suppression to CCG’s stakeholders e.g. GP practices, Local Authorities. Where such data is provided there are safeguards in place to ensure that the receiving organisation has recognised the required safety controls required, i.e. signed agreements from the receiving organisation regarding compliance with data protection and the agreed use of the data. eMBED will flow outputs, mostly in the form of reports to the CCG stakeholders. CCGs may also provide their stakeholders with the anonymised outputs. The anonymisation will be achieved by aggregating records and using small number suppression in line with HES analysis guidance. eMBED provides a range of Business Intelligence functions and outputs as specified by the CCG. These outputs can be presented in a variety of different ways to a variety of different users, from highly aggregated graphical “dashboards” to very low-level tabular analysis, and everything in between with the opportunity to drill-down into the detail. Provision of aggregated reports only with small number suppression data to CCG stakeholders allows for analysis at an appropriate level, revealing potentially useful but previously unrecognised commissioning insights/trends whilst mitigating against the risk of re-identification of individuals 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports including high flyers. The PCU produces a number of reports which provide a summary (not patient level data) which are shared back to the CCG, the following are a list of these: IAPT Dataset Mandated national contract KPIs: Completion of IAPT Minimum Data Set outcome data IAPT Access Times – 6 & 18 wk (finished treatment) Local CCG and NHSE information and KPIs: Number of Referrals Number Entering Treatment Monthly Prevalence rate Number completing treatment Number moving to recovery Number not at caseness Monthly Recovery rate Reliable Improvement rate IAPT Access Times – 6 & 18 wk (entering treatment) Waiting times for treatment and those still waiting Clearance times Local CCG monitoring: Appointments, cancellations and DNA rate analysis Data Quality Referral rates and activity by GP Practice and Age band Mental Health Dataset Mandated national contract KPIs : Completion of valid NHS number field Completion of Ethnic coding Under 16 bed days on Adult wards (Never event) Local CCG and NHSE information and KPIs: Gatekeeping admissions 7 day follow-up hospital discharges EIP access rates Eating disorders Local CCG monitoring: Referral rates by GP Practice and Age band CPA monitoring inc settled accommodation and employment CPA reviews within 12 months, step up/down etc Bed days, admissions and discharges Delayed discharges Detentions LD/ MH/CAMHS ward stays Bed locality (distance out of area) Contacts and DNA rates Cluster monitoring and red rules Data quality The PCU will also share aggregated reports only with small number suppression back to the provider. The PCU shares aggregated reports only with small number suppression outputs with NHS England for national reporting and to support any issues that need rising in relation to data quality.

Processing:

1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes. 2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and Yorkshire DSCRO and the pseudonymised data is then passed securely to North of England CSU. 3. North of England CSU then securely transfer the processed, pseudonymised and linked data to eMBED. 4. eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data would include the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning: • Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT • Mental Health (MHSDS, MHLDDS, MHMDS) with SUS • Improving Access to Psychological Therapies (IAPT) with SUS • Diagnostic Imaging Dataset (DIDs) with SUS • Maternity (MSDS) with SUS • Children and Young People’s Health Services (CYPHS) with SUS 5. Aggregation of required data for CCG management use is completed by eMBED or the CCG as instructed by the CCG. 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared.


Project 6 — DARS-NIC-90713-T3K1V

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 — 2020/02.

Repeats: Frequent adhoc flow, Frequent Adhoc Flow

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 Invoice validation is part of a process by which providers of care or services get paid for the work they do. Invoices are submitted to the Clinical Commissioning Group (CCG) so they are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets and will not be used further. The legal basis for this to occur is under Section 251 of NHS Act 2006. Invoice Validation with be conducted by North of England Commissioning Support Unit. The CCG are advised by North of England Commissioning Support Unit whether payment for invoices can be made or not. Risk Stratification Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes. To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides 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. The legal basis for this to occur is under Section 251 of NHS Act 2006 (CAG 7-04(a)). Risk Stratification will be conducted by eMBED Health Consortium. 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) 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 eMBED Health Consortium.

Expected Benefits:

Invoice Validation 1. Financial validation of activity 2. CCG Budget control 3. Commissioning and performance management 4. Meeting commissioning objectives without compromising patient confidentiality 5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care Risk Stratification Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised: 1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early intervention. 3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care. 5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes. All of the above lead to improved patient experience through more effective commissioning of services. Commissioning 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.

Outputs:

Invoice Validation 1. Addressing poor data quality issues 2. Production of reports for business intelligence 3. Budget reporting 4. Validation of invoices for non-contracted events Risk Stratification 1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. 3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level. 4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient. 5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to: o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost o Plan work for commissioning services and contracts o Set up capitated budgets o Identify health determinants of risk of admission to hospital, or other adverse care outcomes. Commissioning 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers. 9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11. Contract Management and Modelling 12. Patient Stratification, such as: o Patients at highest risk of admission o Most expensive patients (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community

Processing:

Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. All access to data is managed under Roles-Based Access Controls. 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 i.e: 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. Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors. Invoice Validation 1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the North of England Commissioning Support Unit. 3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data. b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between North of England Commissioning Support Unit CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Risk Stratification 1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to 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. Once eMBED Health Consortium 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) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor – eMBED Health Consortium via 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), and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North of England Commissioning Support Unit. 2. North of England Commissioning Support Unit add derived fields, link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning b. Check recorded activity against contracts or invoices and facilitate discussions with providers c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contained within point 1. 4. North of England Commissioning Support Unit then pass the processed, pseudonymised and linked data to both eMBED Health Consortium and the CCG. eMBED Health Consortium 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 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 as set out within NHS Digital guidance applicable to each data set.


Project 7 — DARS-NIC-204520-B1V2G

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

Sensitive: Non Sensitive

When: 2019/05 — 2019/12.

Repeats: System Access

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

Categories: Anonymised - ICO code compliant

Datasets:

  • National Cancer Waiting Times Monitoring DataSet (CWT)

Objectives:

Improvements for Cancer patients The independent Cancer Taskforce set out an ambitious vision for improving services, care and outcomes for everyone with Cancer: fewer people getting Cancer, more people surviving Cancer, more people having a good experience of their treatment and care, whoever they are and wherever they live, and more people being supported to live as well as possible after treatment has finished. Cancer Alliances Cancer Alliances, which have been set up across England, are key to driving the change needed across the country to achieve the Taskforce’s vision. Bringing together local clinical and managerial leaders from providers and commissioners who represent the whole Cancer pathway, Cancer Alliances provide the opportunity for a different way of working to improve and transform Cancer services. Cancer Alliance partners will take a whole population, whole pathway approach to improving outcomes across their geographical ‘footprints’, building on their relevant Sustainability and Transformation Plans (STPs). They will bring together influential local decision-makers and be responsible for directing funding to transform services and care across whole pathways, reducing variation in the availability of good care and treatment for all people with Cancer, and delivering continuous improvement and reduction in inequality of experience. They will particularly focus on leading transformations at scale to improve survival, early diagnosis, patient experience and long-term quality of life. Successful delivery will be shown in improvements in ratings in the Clinical Commissioning Group (CCG) Improvement and Assessment Framework (IAF), including, importantly, in the 62 day wait from referral to first treatment standard. https://www.england.nhs.uk/publication/ccg-iaf-methodology-manual/ Cancer Wait Times (CWT) system The Cancer Wait Times (CWT) system collects and validates the National Cancer Waiting Times Monitoring Data Set (NCWTMDS), allowing performance to be measured against operational Cancer standards. Data is validated and records merged to the same pathway to cover the period from referral to first definitive treatment for Cancer and any additional subsequent treatments. The CWT system then determines whether the operational standard(s) that apply were met or not for the patient and the accountable provider(s). The CWT system holds NCWTMDS in a series of pre-aggregated static reports. These reports are available monthly and quarterly data (aligned with the National Statistics for Cancer Waiting Times published by NHS England). Users can query the CWT system to generate reports to feedback on the progress towards meeting these targets. West Yorkshire and Harrogate Cancer Alliance Wakefield CCG will directly access the Cancer Waiting Times System on behalf of West Yorkshire and Harrogate Cancer Alliance across West Yorkshire and Harrogate. West Yorkshire and Harrogate Cancer Alliance is hosted by Wakefield CCG and covers a population of 2.7 million people. Wakefield CCG works with health organisations across West Yorkshire and Harrogate including 6 acute providers, 9 clinical commissioning groups, 3 community providers and 9 hospices. Acute Providers Airedale NHS Foundation Trust Bradford Teaching Hospitals NHS Foundation Trust Calderdale and Huddersfield NHS Foundation Trust Harrogate and District NHS Foundation Trust Leeds Teaching Hospitals NHS Trust Mid Yorkshire Hospitals NHS Trust CCGs NHS Airedale, Wharfdale and Craven CCG NHS Bradford City CCG NHS Bradford Districts CCG NHS Calderdale CCG NHS Greater Huddersfield CCG NHS Harrogate and Rural District CCG NHS Leeds CCG NHS North Kirklees CCG NHS Wakefield CCG Community Providers Bradford District Care Trust Leeds Community Healthcare NHS Trust Locala Hospices Manorlands, Bradford Marie Curie Hospice, Bradford Overgate Hospice, Calderdale St Micheals, Harrogate Kirkwood Hospice, Huddersfield St Gemma's, Leeds Wheatfield House, Leeds Wakefield Hospice The Prince of Wales Hospice, Pontefract Data access The CWT system provides one organisation (the lead organisation) representing each Cancer Alliance, with access to the following; a) Aggregate reports (which may include unsuppressed small numbers) b) Pseudonymised record level data - users can directly download this data from the CWT system c) I-View Plus tool Lead organisations will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. This Cancer Alliance is limited to West Yorkshire and Harrogate Cancer Patients. A) Aggregate reports including small numbers Aggregate data is available in the form of reports at Provider (Trust) and Clinical Commissioning Group (CCG) level. Small numbers may be included in the aggregate data reports and are essential for analyses carried out by lead organisations. Investigating breaches Lead organisations routinely monitor performance and standards using the CWT system, particularly in relation to breaches of the 62 day wait target. Due to the large number of potential Trust/CCG combinations, breach counts could result in small numbers as in some cases there are less than 6 breaches in a whole year. Given that financial penalties are linked to target breaches counts must accurately reflect the true percentage without suppression. Mitigating risk of re-identification Risk of disclosure is minimised as the dataset does not include patient demographics (increasing risk of re-identification) that may allow users to identify an individual e.g. there are no age, ethnic categories or geographic breakdowns. Additionally, the aggregation categories are such that the data is not at a lesser granular level e.g. the source NCWTMDS data collects information at ICD diagnosis code level, but the CWT system aggregates at tumour group level – e.g. Head & Neck, Upper GI, lower GI, Breast etc. B) Pseudonymised record level extracts Lead organisations will access record level pseudonymised data which includes the system generated pseudo CWT patient ID. Any record level data extracted from the system will not be processed outside of the authorised users of the system. C) i-View Plus . iView Plus uses cube functionality to allow lead organisations to produce graphs, charts and tabulations from the data through the construction of queries. The data in iView plus is split by operational standard being measured and can then be analysed against a range of dimensions collected in the data and measures such as count, percentage and median. The outputs of iView Plus are aggregate, and no record level data can be obtained, however some queries may result in small numbers and these currently have limited disclosure control applied, see A) for further explanation. iView Plus holds published data, the lowest organisational granularity is trust level, data can also be aggregated to CCG level and other health hierarchies. Lead organisations will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements. Lead organisations use of the data will fall into two separate categories, each requiring different levels of suppression, and onward sharing both within the Cancer Alliance and with wider NHS stakeholders; Purpose One - Aggregate local reports Generation of routine Cancer Waiting Times reports at Provider (Trust) or CCG level. Lead organisations will access a summary of the totals for the Providers (Trust) and CCGs that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCGs they are aligned to). This analysis would then be shared with the providers and commissioners and used to inform service improvement by providing benchmarked comparable data. The format of this report would be in a tabulated or graphical form (i.e. not record level) but may contain small numbers. An example of where small numbers would not be suppressed would be in relation to cases of breaches against a standard where small numbers would be essential to ensure the report is meaningful. Examples of this type of analysis include: a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs across the geography b. Analysis of Cancer Waiting Times performance by treatment modality c. Grouping length of waits for standards d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered) f. Analysis of flows of patients including analysis by provider trust site g. Reviewing waits between surgery and radiotherapy for Head and Neck Cancer patients with a maximum recommended wait of 6 weeks h. Reviewing routes to diagnosis of patients i. Quantifying treatment volumes by provider organisation including analysis treatment rates Purpose Two - Sharing of record level data (including free text breach reasons) with providers and commissioners responsible for direct patient care for that patient. This will be for local clinical audit purposes. The two broad purposes for this would be; 1) To support local clinical audit work 2) Investigate individual outliers to the national standards Pathway analysis will be undertaken, identifying trends in reasons for breaches. The analysis will inform system wide pathway improvements and compliance to the national standards. Examples of potential changes to achieve this could be to support trusts in additional resources and processes and also to facilitate discuss between trusts for example in reaching agreement for diagnostics between trusts. Examples of the types of reasons for this include; a. Patients waiting excessively long period of time to seen of received treatment b. Free text breach reasons identifying areas of concern which require more detail or clarification from provider c. Identification of 28 day standard exceptions - National guidance states patients who are diagnosed with cancer should be informed face to face, this would highlights numbers of patients who are not told in person by provider d. Audits to review orphan records which require local providers to review local patients records Record level data (pseudonymised) will be shared via NHS.net email accounts and access will be controlled by password protecting all files.

Yielded Benefits:

To date West Yorkshire and Harrogate Cancer Alliance has mainly received cancer waits data in the form of pre-analysed reports from NHS England. These have enabled the Alliance and its Board to identify priority pathways and parts of pathways for remedial action to deliver improved clinical pathways and faster diagnosis and treatment. To date there has been no specific use of data from the Open Exeter system.

Expected Benefits:

1) Benefits type: Supporting delivery of CWT standards The Cancer Waiting Times standards are key operational standards for the NHS, which aim to reduce the waits for diagnosis and treatment for Cancer patients, which will support improvements to survival rates and improve patient experience. This includes the new 28 day faster diagnosis standard being introduced as a standard from April 2020. A key enabler to achieve these standards, and thus improve survival and patient experience is the role of Cancer Alliances locally to work with providers and commissioners to improve patient pathways. Access to the Cancer Waiting Times data as detailed in the above will enable Cancer Alliances to have informed discussions and allocate resources optimally to improve performance against these standards. It will also enable Cancer Alliances to work with local providers and commissioners to identify outliers against the standards, and mitigate the risk of similar delays for other patients. Improvement would be expected on an on-going basis with standards already in place for nine standards:- • 2 week wait urgent GP referral – 93% • 2 week wait breast symptomatic – 93% • 31 day 1st treatment - 96% • 31 day subsequent surgery – 94% • 31 day subsequent drugs – 98% • 31 day subsequent radiotherapy – 94% • 62 day (GP) referral to 1st treatment – 85% • 62 day (screening ) referral to 1st treatment – 90% • 62 day upgrade to 1st treatment – locally agreed standard In addition this access and use of data will be key in delivering the new 28 day faster diagnosis standard being introduced from 2020 2) Benefits type: Improvements beyond constitutional standards This access and resulting analysis will enable Cancer Alliances to undertake local analysis beyond the Cancer Waiting times operational standards to support improvements to Cancer patients pathways beyond those already achieved by improving performance against standard set. This could include reviewing times between treatments, or treatment rates. The overall aim of this type of additional analysis would be to support improvements to Cancer patients survival and experience. The Cancer Taskforce recommendation set out a number of ambitions to be met nationally and locally by 2020 including improving 1 year survival for Cancer to 75%, and improving the proportions of patients staged 1 or 2 to 62%. For both of these improvements to the diagnostic and treatment pathways are key, and require Cancer Alliances to be able to analyse the Cancer Waiting Times dataset to identify sub-optimum pathways and resulting improvements.

Outputs:

Outputs fall into the following categories: 1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs. b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays. e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered) f. Analysis of flows of patients including analysis by provider trust site g. Outlier identification including exceptionally long waits to inform individual queries to providers 2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patient’s outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust. The overarching aim of all future analysis/outputs is to inform priorities and potential investment to improve Cancer pathways including reducing Cancer incidence and mortality, improving Cancer survival, improving patient experience, improving service efficiency and meeting national constitution standards relating to Cancer patients.

Processing:

Access to the Cancer Wait Times (CWT) System will enable Cancer Alliances to undertake a wide range of locally-determined and locally-specific analyses to support the Cancer Taskforce vision for improving services, care and outcomes for everyone with Cancer. As Wakefield CCG are acting as the lead organisation in a Cancer Alliance their access is via the same route as other Cancer Alliances i.e via the Cancer Wait Times (CWT) System. The team doing this processing within Wakefield CCG are separate from the the commissioning team and would not have access to data provide via the DSCRO route. Additionally any separate agreement that Wakefield CCG have to access CWT may include other processors and purposes. Only the lead organisation Wakefield CCG will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the Wakefield CCG servers. Role Based Access Control prevents access to data downloads to employees outside of the analytical team responsible for producing outputs; the Health and Care Partnership Analytics Team and Wakefield CCG analytics team. The CWT system is hosted by NHS Digital, access to and usage of the system is fully auditable. Users must comply with the use of the data as specified in this agreement. The CWT system complies with the requirements of NHS Digital Code of Practice on Confidential Information, the Caldicott Principles and other relevant statutory requirements and guidance to protect confidentiality. 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. Access to the CWT system will be granted to individual users only when a valid Data Usage Certificate (DUC) form is submitted to NHS Digital via the lead organisations Senior Information Risk Officer (SIRO), and where there is a valid Data Sharing Agreement between the lead organisation and NHS Digital. Approved users will log into the system via an N3 connection and will use a Single Sign-On (users are prompted to create a unique username and password). Wakefield CCG users will access: a) Aggregate reports (which may include unsuppressed small numbers) b) Pseudonymised record level data - users can directly download this data from the CWT system c) I-View Plus tool (aggregated - access to produce graphs, charts/tabulations from the data through the construction of queries). This will give users access to run bespoke analysis on pre-defined measures and dimensions. It delivers the same data that is available through the reports and record level downloads (i.e. it will not contain patient identifiable data). Any record level data extracted from the system will not be processed outside of Wakefield CCG unless otherwise specified in this agreement. Following completion of the analysis the record level data will be securely destroyed. Users are not permitted to upload data into the system. Data will only be available for the Providers (Trust) and CCGs that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCGs that this Cancer Alliance is aligned to). The data will only be shared with other members of the Cancer Alliance in the format described in purpose 1 and purpose 2 of this agreement. The primary method for sharing outputs is nhs.net email. Aggregate data/ graphical outputs may be shared via e-mail; for example as part of Alliance meeting papers. Where record level data is shared with individual trusts these are shared only with trust(s) who were involved in the direct care of the patient, only via NHS.net email accounts. Data will only be shared as described in purpose one and purpose two of this agreement and where recipient organisations hold a valid Data Sharing Agreement with NHS Digital to access Cancer Waiting Times data. Training on the CWT system is not required as it is a data delivery system and it does not provide functionality to conduct bespoke detailed analysis. User guides are available for further assistance. Access to the CWT system data is restricted to Cancer Alliance employees who are substantively employed by the Data Controller in fulfilment of their public health function. The Cancer Alliances will use the data to produce a range of quantitative measures (counts, crude and standardised rates and ratios) that will form the basis for a range of statistical analyses of the fields contained in the supplied data. Typical uses will include: 1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs. b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays. e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered) f. Analysis of flows of patients including analysis by provider trust site g. Outlier identification including exceptionally long waits to inform individual queries to providers 2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patient’s outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust. The members of the Health and Care Partnership Analytics Team who will process the data are all substantive employees of Wakefield CCG.


Project 8 — DARS-NIC-125783-W2W3P

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

Sensitive: Sensitive

When: 2019/03 — 2020/02.

Repeats: Frequent Adhoc Flow

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

Categories: Anonymised - ICO code compliant

Datasets:

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

Objectives:

Multi-specialty Community Provider (MCP) Vanguard The primary objective for processing is to enable a robust evaluation of the MCP Vanguard interventions, in order to inform future service planning and resource allocation. The primary activities within the vanguard will be establishing evening and weekend GP appointments, ensuring direct access to a physiotherapist for people with muscle and joint problems, having pharmacists work alongside health workers to make sure people get the right medicine, making use of video and email consultations, including the use of video technology to enable GPs and hospital clinicians to provide enhanced care in care homes, creating an electronic service directory and a wide range of apps to help people stay healthy and find the right service for them. Using the data requested, the intention is to determine what impact the MCP Vanguard interventions are having on different elements of an individual’s care. This evidence will support future service delivery, but also provide the national new models of care team with information to enable them to determine the optimum service design that should be used for national roll out. The main outcomes being looking at, will be the impact on secondary care activity, namely hospital admissions, A&E attendance, length of stay in hospital and whether an impact has been seen on the ambulance service regarding reduced demand, as many of the interventions are aimed at reducing this activity and subsequently the cost to the health system. Enhanced Health Care Homes (EHCH) Vanguard The primary objective for processing is to enable a robust evaluation of the Care Home Vanguard interventions, in order to information future service planning and resource allocation. This requires a dataset purely about the residents of care homes, and then linking their activity with several different services in order to understand the full spectrum of care that they receive. The intention is to determine the impact the EHCH vanguard interventions are having on different elements of an individual’s care. This evidence will support future service delivery, but also provide the national new models of care team with information to enable them to determine the optimum design that should be used for national roll out. The main outcomes being looking at will be the impact on secondary care activity, namely hospital admissions, A&E attendance, length of stay in hospital and whether an impact has been seen on the ambulance service regarding reduced demand, as many of the interventions are aimed at reducing this activity and subsequently the cost to the health system. Evaluation of whether the vanguard is impacting the ambulance service by seeing reduced demand and whether end of life care is improving. The EHCH Vanguard will specifically relate to care home patients in the Wakefield locality and a number of schemes are specific to the EHCH vanguard. This will impact on the outcomes described above and evaluation will need to occur on these EHCH specific schemes. Therefore there is a need for two vanguards,. However, it should be mentioned that the EHCH vanguard is a subset of the MCP vanguard. The MCP schemes also has an impact on the EHCH vanguard outcomes, in addition to the EHCH schemes.

Expected Benefits:

MCP Vanguard The information will allow the MCP and EHCH vanguards to understand the Health and Care need in an integrated manner. Showing areas of need that have not been highlighted previously in the area. Understanding patient journeys in a more complete manner will allow the services to better plan and improve services to meet the need of the residents better. It will allow understanding of the pinch point across the system between differing services. Showing which services are more effective at address need and help forecast the likely changing demands from the population. EHCH Vanguard The information will allow the MCP and EHCH vanguards to understand the Health and Care need in an integrated manner. Showing areas of need that have not been highlighted previously in the area. Understanding patient journeys in a more complete manner will allow the services to better plan and improve services to meet the need of the residents better. It will allow understanding of the pinch point across the system between differing services. Showing which services are more effective at address need and help forecast the likely changing demands from the population.

Outputs:

MCP Vanguard End of year evaluation report. This will include analysis of the impacts that have been made on the following: • Secondary care activity (admissions, A&E, bed days, ambulance service demand) • Community services • Mental Health services Other outputs will be aggregated around individuals with specific conditions or service interventions they have received EHCH Vanguard End of year evaluation report. This will include analysis of the impacts that have been made on the following: • Secondary care activity (admissions, A&E, bed days, ambulance service demand) • Community services • Mental Health services • Mortality of care home residents Other outputs will be aggregated around individuals with specific conditions or service interventions they have received Specific to the EHCH vanguard, the majority of outputs will be aggregated, based around the care homes who are in scope and out of scope (over 500 residents in each cohort) The data will also be used for monthly reporting against expected 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.   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 the Wakefield 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 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 Wakefield 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. 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) Data Processor 1 – North England Commissioning Support Unit 1) Data quality management and pseudonymisation of SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies (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) and Civil Registries Data (CRD) only is securely transferred from the DSCRO to North of England Commissioning Support Unit and the pseudonymised data is then held until completion of points 2 – 7. 2) North of England CSU also receive GP Data. It is received as follows: a. Identifiable GP data is submitted to the CSU. b. The data lands in a ring fenced area for GP data only. c. There is a Data Processing Agreement in place between the GP practice and the CSU. A specific named individual within the CSU acts on behalf on the GP practice. This person has been issued with a black box. d. The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to the pseudonymisation request. The individual does not have access to the data once it has been passed on to the CSU. e. The GP data is then pseudonymised using the black box and DSCRO issued key – the clear data is then deleted from the ring fenced area. f. The CSU are then sent the identifiable GP data with the pseudo key specific to the request. 3) North of England CSU also receive a pseudonymised flow of social care data from Wakefield Council . Social Care data is received as follows: a. Wakefield Council is issued with their own black box solution. b. Wakefield Council requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to Wakefield Council and the pseudonymisation request. c. Wakefield Council submit the pseudonymised social care data to the CSU with the pseudo algorithm specific to them. 4) Once the pseudonymised GP data and/or social care data is received, the CSU make a request to the DSCRO. 5) The DSCRO send a mapping table to the CSU 6) The CSU overwrite the organisation specific keys with the DSCRO-provided CSU keys. 7) The mapping table is then deleted. 8) The DSCRO then pass the pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies (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) and Civil Registries Data (CRD) securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis. 9) Social care and/or GP data is then linked to the data sets listed within point 8 in the CSU 10) Aggregation of required data for CCG management use will be completed by the CSU as instructed by the CCG. 11) The linked pseudonymised data is securely passed to Data Processor 2 – eMBED and Data Processor 3 Wakefield Council and NHS Wakefield CCG. Data Processor 2– Kier Business Services and Dr Foster (Hosting the eMBED Health Consortium) 12) North of England Commissioning Support Unit then securely send the pseudonymised and linked data to eMBED Health Consortium (hosted by Kier Business Services and Dr Foster). The eMBED Health Consortium analyse data to: a. See patient journeys for pathways or service design, re-design and de-commissioning. • Supporting the CCG with the development with its Primary Care Home Model of care, by understanding the population needs, demands and outcomes in depth for each of the primary care homes across the Wakefield system. • Help shape commissioning processes to be place based, patient centred for health and social care providers locally. • Support the system to evaluate interventions, services and projects. b. Undertake population health management • Provide insight and intelligence into the population needs and health and care demand for the Wakefield health and care system. • As an example meeting districts recent strategic request to better understand, the complete patient experience of respiratory care pathways across the Wakefield system from health and social care providers. c. Conduct Health Needs Assessments and thoroughly investigate the needs of the population • Articulate the changing levels of population need for health and care services for respiratory care, again as an recent example. • Support the local Joint Strategic needs Assessment Process, by provider more complete understanding of population need from their conditions and journeys through care pathways across the Wakefield system. d. Understand cohorts of residents who are at risk • Implement existing models of risk and approaches to segmentation in line with the Population Health Management approach being rolled out by NHS E • Develop local risk models and predictive analytics for support preventative activity. 13) eMBED Health Consortium (hosted by Kier Business Services and Dr Foster) then pass the processed, pseudonymised and linked data to Wakefield Council and the CCG. Data Processor 3 - Wakefield Council 14) Wakefield Council analyse data to: a. See patient journeys for pathways or service design, re-design and de-commissioning. • Supporting the CCG with the development with its Primary Care Home Model of care, by understanding the population needs, demands and outcomes in depth for each of the primary care homes across the Wakefield system. • Help shape commissioning processes to be place based, patient centred for health and social care providers locally. • Support the system to evaluate interventions, services and projects. b. Undertake population health management • Provide insight and intelligence into the population needs and health and care demand for the Wakefield health and care system. • As an example meeting districts recent strategic request to better understand, the complete patient experience of respiratory care pathways across the Wakefield system from health and social care providers. c. Conduct Health Needs Assessments and thoroughly investigate the needs of the population • Articulate the changing levels of population need for health and care services for respiratory care, again as an recent example. • Support the local Joint Strategic needs Assessment Process, by provider more complete understanding of population need from their conditions and journeys through care pathways across the Wakefield system. d. Understand cohorts of residents who are at risk • Implement existing models of risk and approaches to segmentation in line with the Population Health Management approach being rolled out by NHS England. • Develop local risk models and predictive analytics for support preventative activity. 15). Wakefield Council then pass the processed, pseudonymised and linked data to the CCG. 16) Aggregation of required data for CCG management use will be completed by eMBED Health Consortium (hosted by Kier Business Services and Dr Foster), Wakefield Council or the CCG as instructed by the CCG. 17) 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.