NHS Digital Data Release Register - reformatted

NHS Brighton And Hove Ccg

🚩 NHS Brighton And Hove Ccg received multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Brighton And Hove 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-43430-K7G1D

Opt outs honoured: Y, N

Sensitive: Sensitive

When: 2016/12 — 2017/11.

Repeats: Ongoing

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

Categories: Identifiable, Anonymised - ICO code compliant

Datasets:

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

Objectives:

Risk Stratification This is an application to use SUS data identifiable at the level of NHS number for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Pseudonymised – SUS and Local Flows Application for the CCG to use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs 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. No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

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

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

Processing:

South London DSCRO (part of NHS Digital) will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO. Risk Stratification 1. Identifiable SUS data is obtained from the SUS Repository to South London Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management and standardisation of data is completed by South London DSCRO and the data identifiable at the level of NHS number is transferred securely to South East CSU, who hold the SUS data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to South East CSU. 4. SUS data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 6. South East CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication. 7. Once South East CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level. Pseudonymised – SUS and Local Flows Data Processor 1 (South East CSU) 1. South London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. South London 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 South East CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows 3. South East CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG. 5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place. Data Processor 2 (South, Central and West CSU) 1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. South Collaborative 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 South Central and West CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows 3. South Central and West CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG. 5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place. Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS Data Processor 1 (South East CSU) 1. South London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, 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 and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to South East CSU for the addition of derived fields and analysis. 3. South East CSU then pass the processed, pseudonymised data to the CCG. 4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning 5. Aggregation of required data for CCG management use will be 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 where contractual arrangements are in place. Data Processor 2 (South, Central and West CSU) 1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, 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 and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields and analysis. 3. South Central and West CSU then pass the processed, pseudonymised data to the CCG. 4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning 5. Aggregation of required data for CCG management use will be 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 where contractual arrangements are in place.


Project 2 — NIC-169933-S9N9J

Opt outs honoured: N

Sensitive: Sensitive

When: 2018/03 — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • 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
  • Mental Health Services Data Set
  • Mental Health Minimum Data Set
  • Mental Health and Learning Disabilities Data Set
  • Maternity Services Data Set
  • Improving Access to Psychological Therapies 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
  • Community Services Data Set
  • Children and Young People Health
  • Ambulance-Local Provider Flows
  • Acute-Local Provider Flows

Objectives:

Commissioning The NHS and local councils have come together in 44 areas covering all of England to develop proposals to improve health and care. They have formed new partnerships – known as sustainability and transformation partnerships – to plan jointly for the next few years. Sustainability and transformation partnerships build on collaborative work that began under the NHS Shared Planning Guidance for 2016/17 – 2020/21, to support implementation of the Five Year Forward View. They are supported by six national health and care bodies: NHS England; NHS Improvement; the Care Quality Commission (CQC); Health Education England (HEE); Public Health England (PHE) and the National Institute for Health and Care Excellence (NICE). The CCG is part of the Sussex and East Surrey Sustainable Transformation Partnership. The STP is responsible for implementing large parts of the 5 year forward view from NHS England. The STP is implementing several initiatives: - Putting the patient at the heart of the health system - Working across organisational boundaries to deliver care and including social care, public Health, providers and GPs as well as CCGs - Reviewing patient pathways to improve patient experience whilst reducing costs e.g. reduce the number of standard tests a patient may have and only have the ones they need - Planning the demand and capacity across the healthcare system across 8 CCGs to ensure we have the right buildings, services and staff to cope with demand whilst reducing the impact on costs - Working to prevent or capture conditions early as they are cheaper to treat - Introduce initiatives to change behaviours e.g. move more care into the community - Patient pathway planning for the above To ensure the patient is at the heart of care, the STP is focussing on where services are required across the geographical region. This assists to ensure delivery of care in the right place for patients who may move and change services across CCGs. The CCG will work proactively and collaboratively with the other CCGs in the STP to redesign services across boundaries to integrate services. Collaborative sharing is required for CCGs to understand these requirements. The CCGs will 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 STP 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 - Ensuring we do what we should - 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 - South, Central and West Commissioning Support Unit

Expected Benefits:

Commissioning 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities. 14. Reviewing current service provision a. Cost-benefit analysis and service impact assessments to underpin service transformation across health economy b. Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.) c. Impact analysis for different models or productivity measures, efficiency and experience d. Service and pathway review e. Service utilisation review 15. Ensuring compliance with evidence and guidance a. Testing approaches with evidence and compliance with guidance. 16. Monitoring outcomes a. Analysis of variation in outcomes across population group 17. Understanding how services impact across the health economy a. Service evaluation b. Programme reviews c. Analysis of productivity, outcomes, experience, plan, targets and actuals d. Assessing value for money and efficiency gains e. Understanding impact of services on health inequalities 18. Understanding how services impact on the health of the population and patient cohorts a. Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this b. Propensity matching and scoring c. Triple aim analysis 19. Understanding future drivers for change across health economy a. Forecasting health and care needs for population and population cohorts across STPs b. Identifying changes in disease trends and prevalence c. Efficiencies that can be gained from procuring services across wider footprints, from new innovations d. Predictive modelling 20. Delivering services that meet changing needs of population a. Analysis to support policy development b. Ethical and equality impact assessments c. Implementation of NMOC d. What do next years contracts need to include? e. Workforce planning 21. Maximising services and outcomes within financial envelopes across health economy a. What-if analysis b. Cost-benefit analysis c. Health economics analysis d. Scenario planning and modelling e. Investment and disinvestment in services analysis f. Opportunity analysis

Outputs:

Commissioning 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers. 9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11. Contract Management and Modelling 12. Patient Stratification, such as: o Patients at highest risk of admission o Most expensive patients (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community 13. Profiling population health and wider determinants to identify and target those most in need a. Understanding population profile and demographics b. Identify patient cohorts with specific needs or who may benefit from interventions c. Identifying disease prevalence. health and care needs for population cohorts d. Contributing to Joint Strategic Needs Assessment (JSNA) e. Geographical mapping and analysis 14. Identifying and managing preventable and existing conditions a. Identifying types of individuals and population cohorts at risk of non-elective re-admission b. Risk stratification to identify populations suitable for case management c. Risk profiling and predictive modelling d. Risk stratification for planning services for population cohorts e. Identification of disease incidence and diagnosis stratification 15. Reducing health inequalities a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs b. Socio-demographic analysis 16. Managing demand a. Waiting times analysis b. Service demand and supply modelling c. Understanding cross-border and overseas visitor d. Winter planning e. Emergency preparedness, business continuity, recovery and contingency planning 17. Care co-ordination and planning a. Planning packages of care b. Service planning c. Planning care co-ordination 18. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system a. Patient pathway analysis across health and care b. Outcomes & experience analysis c. Analysis to support anti-terror initiatives d. Analysis to identify vulnerable patients with potential safeguarding issues e. Understanding equity of care and unwarranted variation f. Modelling patient flow g. Tracking patient pathways h. Monitoring to support New Models of Care, Accountable Care Organisations and Sustainable Transformation Partnerships i. Identifying duplications in care j. Identifying gaps in care, missed diagnoses and triple fail events k. Analysing individual and aggregated timelines 19. Undertaking budget planning, management and reporting a. Tracking financial performance against plans b. Budget reporting c. Tariff development d. Developing and monitoring capitated budgets e. Developing and monitoring individual-level budgets f. Future budget planning and forecasting g. Paying for care of overseas visitors and cross-border flow 20. Monitoring the value for money a. Service-level costing & comparisons b. Identification of cost pressures c. Cost benefit analysis d. Equity of spend across services and population cohorts e. Finance impact assessment 21. Comparing population groups, peers, national and international best practice a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice b. Benchmarking against other parts of the country c. Identifying unwarranted variations 22. Comparing expected levels a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations 23. Comparing local targets & plan a. Monitoring of local variation in productivity, cost, outcomes, quality and experience b. Local performance dashboards by service provider, commissioner, geography, NMOC, STPs 24. Monitoring activity and cost compliance against contract and agreed plans a. Contract monitoring b. Contract reconciliation and challenge c. Invoice validation 25. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans a. Performance dashboards b. CQUIN reporting c. Clinical audit d. Patient experience surveys e. Demand, supply, outcome & experience analysis f. Monitoring cross-border flows and overseas visitor activity 26. Improving provider data quality a. Coding audit b. Data quality validation and review c. Checking validity of patient identity and commissioner assignment

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. Data cannot be stored in a cloud environment under this agreement. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the Sussex and East Surrey Sustainable Transformation Partnership. No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) Segregation Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. Commissioning The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS 2. Local Provider Flows (received directly from providers) o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening 3. Mental Health Minimum Data Set (MHMDS) 4. Mental Health Learning Disability Data Set (MHLDDS) 5. Mental Health Services Data Set (MHSDS) 6. Maternity Services Data Set (MSDS) 7. Improving Access to Psychological Therapy (IAPT) 8. Child and Young People Health Service (CYPHS) 9. 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 1 - South, Central and West Commissioning Support Unit 1. Pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS) and Diagnostic Imaging data (DIDS) only is held until points 2 – 8 are completed. 2. South, Central and West Commissioning Support Unit receives GP data. GP Data is received as follows: o Identifiable GP data is submitted to South Central and West Commissioning Support Unit. o The identifiable data lands in a ring-fenced area for GP data only. o The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO. o There is a Data Processing Agreement in place between the GP and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the GP. o This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO. o Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted. o South Central and West Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo algorithm specific to them. 3. South, Central and West Commissioning Support Unit also receive a flow of social care data. Social Care data is received in one of the following 2 ways: o Pseudonymised:  Social Care data is pseudonymised within the provider using a pseudonymisation tool, different to that used by the DSCRO. The provider requests a pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the Local Authority and to that specific date.  The pseudonymised data lands in a ring-fenced area for social care data only.  There is a Data Processing Agreement in place between the Provider and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the Provider.  This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.  The data is then passed into the non-ringfenced area with the pseudo algorithm specific to them. o Identifiable:  Identifiable social care data is submitted to South Central and West Commissioning Support Unit.  The identifiable data lands in a ring-fenced area for social care data only.  The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.  There is a Data Processing Agreement in place between the Local Authority and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the provider.  This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.  Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.  South Central and West Commissioning Support Unit are then sent the pseudonymised social care data with the pseudo algorithm specific to them. 4. Once the pseudonymised GP data and social care data is received, South, Central and West Commissioning Support Unit make a request to the DSCRO. 5. The DSCRO check the dates of the key generation (Point 2d and 3aii/3biv). 6. The DSCRO then send a mapping table to South, Central and West Commissioning Support Unit 7. South, Central and West Commissioning Support Unit then overwrite the organisation specific keys with the DSCRO key. 8. The mapping table is then deleted. 9. The DSCRO pass the pseudonymised SUS, local provider data, Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) securely to South, Central and West Commissioning Support Unit for the addition of derived fields, linkage of data sets and analysis 10. GP and Social care data is then linked to the data sets listed within point 9. 11. South, Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. 12. Aggregation of required data for CCG management use will be completed by South, Central and West Commissioning Support Unit as instructed by the CCG. 13. 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 3 — DARS-NIC-91808-P5Z1F

Opt outs honoured: Yes - patient objections upheld, No - DSfC for Invoice Validation Purposes (Section 251, Section 251 NHS Act 2006)

Sensitive: Sensitive

When: 2018/06 — 2021/04.

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

Legal basis: Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'.

Categories: Identifiable

Datasets:

  • SUS for Commissioners

Objectives:

Invoice Validation Invoice validation is part of a process by which providers of care or services get paid for the work they do. Invoices are submitted to the Clinical Commissioning Group (CCG) so 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 South Central and West CSU The CCG are advised by South Central and West CSU whether payment for invoices can be made or not. Risk Stratification Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes. To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care. The legal basis for this to occur is under Section 251 of NHS Act 2006 (CAG 7-04(a)). Risk Stratification will be conducted by North East London Commissioning Support Unit using the Sollis Partnership Ltd risk stratification tool.

Yielded Benefits:

N/A

Expected Benefits:

Invoice Validation 1. Financial validation of activity 2. CCG Budget control 3. Commissioning and performance management 4. Meeting commissioning objectives without compromising patient confidentiality 5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care Risk Stratification Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised: 1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early intervention. 3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care. 5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes All of the above lead to improved patient experience through more effective commissioning of services.

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.

Processing:

Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG. Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. All access to data is managed under Roles-Based Access Controls No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO. CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools. Segregation Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors. Invoice Validation 1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the South Central and West CSU 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 South Central and West 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 1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to North East London Commissioning Support Unit, who hold the SUS+ data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to North East London Commissioning Support Unit. 4. SUS+ data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the Sollis Partnership Ltd risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 6. Access to the Sollis Partnership Ltd Risk Stratification system that North East London Commissioning Support Unit hosts is limited to those substantive employees with authorised user accounts used for identification and authentication.* 7. Once North East London Commissioning Support Unit has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level * Sollis Partnership Ltd provide technical support to their software that is hosted by North East London Commissioning Support Unit. Access is for routine maintenance only. Access will be either on site or remotely through secure N3 link from the Sollis offices or via secure VPN link only using Sollis issued and secured devices. Access is limited to those substantive employees with authorised user accounts used for identification and authentication. Only live data is accessed and data is not copied from the system. Any live data accessed only for maintenance purposes by Sollis staff is pseudonymised. A log of all activity is retained for audit purposes. All Sollis devices and all such remote access sessions are audited and audit logs are reviewed centrally. The Sollis email system will automatically check the content of messages and attachments and then alerts recipients, senders and administrators should any material the system assesses as resembling patient data be transmitted. In such circumstances, any patient identifiable data found on the system will be destroyed.


Project 4 — DARS-NIC-423553-H8D6H

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

Sensitive: Sensitive

When: 2021/01 — 2021/04.

Repeats: One-Off

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Categories: Anonymised - ICO code compliant

Datasets:

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

Objectives:

COMMISSIONING To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) - Local Provider Flows o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Community Services Data Set (CSDS) - Diagnostic Imaging Data Set (DIDS) - National Cancer Waiting Times Monitoring Data Set (CWT) - Civil Registries Data (CRD) (Births) - Civil Registries Data (CRD) (Deaths) - National Diabetes Audit (NDA) - Patient Reported Outcome Measures (PROMs) - e-Referral Service (eRS) - Personal Demographics Service (PDS) - Summary Hospital-level Mortality Indicator (SHMI) The pseudonymised data is required to for the following purposes: § Population health management: · Understanding the interdependency of care services · Targeting care more effectively · Using value as the redesign principle § Data Quality and Validation – allowing data quality checks on the submitted data § Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them § Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs § Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated § Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another § Service redesign § Health Needs Assessment – identification of underlying disease prevalence within the local population § Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models § Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand. § Support measuring the health, mortality or care needs of the total local population 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 NHS South, Central and West Commissioning Support Unit And Optum Health Solutions (UK) Limited.

Expected Benefits:

COMMISSIONING 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities. 14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed. 15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice. 16. Provision of indicators of health problems, and patterns of risk within the commissioning region. 17. Support of benchmarking for evaluating progress in future years. 18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 19. Assists commissioners to make better decisions to support patients and drive changes in health care 20. Allows comparisons of providers performance to assist improvement in services – increase the quality 21. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 23. Monitoring of entire population, as a pose to only those that engage with services 24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice. 25. Monitor the quality and safety of the delivery of healthcare services. 26. Allow focused commissioning support based on factual data rather than assumed and projected sources

Outputs:

COMMISSIONING 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports. 9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11. Contract Management and Modelling 12. Patient Stratification, such as: o Patients at highest risk of admission o High cost activity uses (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community 13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services. 14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die. 15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support. 16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust. 17. Removal of patients from Risk Stratification reports. 18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity. 19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand. 20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals. 22. Allow Commissioners to better protect or improve the public health of the total local patient population 23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population 24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 25. Investigate mortality outcomes for trusts

Processing:

PROCESSING CONDITIONS: Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake. Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification. CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools. The identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship. ONWARD SHARING: Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set. SEGREGATION: Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. DATA MINIMISATION: Data Minimisation in relation to the data sets listed within the application are listed below. This also includes the purpose on which they would be applied - For the purpose of Commissioning: • Patients who are normally registered and/or resident within the NHS Brighton and Hove CCG, NHS East Sussex CCG and NHS West Sussex CCG regions (including historical activity where the patient was previously registered or resident in another commissioner). and/or • Patients treated by a provider where NHS Brighton and Hove CCG, NHS East Sussex CCG and NHS West Sussex CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows. and/or • Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of NHS Brighton and Hove CCG, NHS East Sussex CCG and NHS West Sussex CCG - this is only for commissioning and relates to both national and local flows. In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement. A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation). University Hospitals Bristol NHS Foundation Trust 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." Microsoft Limited provide cloud services for South Central and West Commissioning Support Unit and are therefore listed as processors. 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. Microsoft Limited and Amazon Web Services provide cloud services for Optum Health Solutions (UK) Limited and are therefore listed as processors. 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. ANS Group Limited will be assisting in the set up and management of the South Central and West Commissioning Support Unit Microsoft Azure Cloud and are therefore listed as a data processor. They will not have any additional processing / storage addresses (as these will be the Microsoft Azure addresses). Using the data for any other purpose would be considered a breach of this agreement. COMMISSIONING The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS+ 2. Local Provider Flows (received directly from providers) a. Acute b. Ambulance c. Community d. Demand for Service e. Diagnostic Service f. Emergency Care g. Experience, Quality and Outcomes h. Mental Health i. Other Not Elsewhere Classified j. Population Data k. Primary Care Services l. Public Health Screening 3. Mental Health Minimum Data Set (MHMDS) 4. Mental Health Learning Disability Data Set (MHLDDS) 5. Mental Health Services Data Set (MHSDS) 6. Maternity Services Data Set (MSDS) 7. Improving Access to Psychological Therapy (IAPT) 8. Child and Young People Health Service (CYPHS) 9. Community Services Data Set (CSDS) 10. Diagnostic Imaging Data Set (DIDS) 11. National Cancer Waiting Times Monitoring Data Set (CWT) 12. Civil Registries Data (CRD) (Births) 13. Civil Registries Data (CRD) (Deaths) 14. National Diabetes Audit (NDA) 15. Patient Reported Outcome Measures (PROMs) 16. e-Referral Service (eRS) 17. Personal Demographics Service (PDS) 18. Summary Hospital-level Mortality Indicator (SHMI) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 - South, Central and West Commissioning Support Unit 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI) data only is held until points 2 – 8 are completed. 2. South, Central and West Commissioning Support Unit receives GP data. GP Data is received as follows: o Identifiable GP data is submitted to South Central and West Commissioning Support Unit. o The identifiable data lands in a ring-fenced area for GP data only. o The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO. o There is a Data Processing Agreement in place between the GP and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the GP. o This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO. o Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted. o South Central and West Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo algorithm specific to them. 3. South, Central and West Commissioning Support Unit also receive a flow of social care data. Social Care data is received in one of the following 2 ways: o Pseudonymised:  Social Care data is pseudonymised within the provider using a pseudonymisation tool, different to that used by the DSCRO. The provider requests a pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the Local Authority and to that specific date.  The pseudonymised data lands in a ring-fenced area for social care data only.  There is a Data Processing Agreement in place between the Provider and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the Provider.  This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.  The data is then passed into the non-ringfenced area with the pseudo algorithm specific to them. o Identifiable:  Identifiable social care data is submitted to South Central and West Commissioning Support Unit.  The identifiable data lands in a ring-fenced area for social care data only.  The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.  There is a Data Processing Agreement in place between the Local Authority and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the provider.  This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.  Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.  South Central and West Commissioning Support Unit are then sent the pseudonymised social care data with the pseudo algorithm specific to them. 4. Once the pseudonymised GP data and social care data is received, South, Central and West Commissioning Support Unit make a request to the DSCRO. 5. The DSCRO check the dates of the key generation (Point 2d and 3aii/3biv). 6. The DSCRO then send a mapping table to South, Central and West Commissioning Support Unit 7. South, Central and West Commissioning Support Unit then overwrite the organisation specific keys with the DSCRO key. 8. The mapping table is then deleted. 9. The DSCRO pass the pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times (CWT), Civil Registration Data (CRD) (births and deaths), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs),e-Referral Service (eRS), Personal Demographics Service (PDS),Summary Hospital-level Mortality Indicator (SHMI) securely to South, Central and West Commissioning Support Unit for the addition of derived fields, linkage of data sets and analysis 10. GP and Social care data is then linked to the data sets listed within point 9. 11. South, Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. 12. Aggregation of required data for CCG management use will be completed by South, Central and West Commissioning Support Unit as instructed by the CCG. 13. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set. Data Processor 2 - Optum Health Solutions (UK) Ltd - for the NHS England Wave 2 PHM Project 1. Pseudonymised SUS+, Mental Health Services Data Set, Community Services Data Set, Local Flow Provider Data, GP Primary Care data and Social Care data is securely transferred from NHS Brighton and Hove CCG, NHS East Sussex CCG and NHS West Sussex CCG to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national datasets and sent as individual data flows. 2. Optum Health Solutions (UK) Ltd provide analysis to: o Whole population segmentation to assess population health needs o Prospective risk scoring for individuals to indicate the likelihood of future adverse events o Predictive modelling to determine individuals at risk and an understanding of the drivers of risk o Longitudinal analysis of intersegmental drift - identifying individuals who move between complexity classifications and the drivers of these transitions o The production of individual-level theographs to identify gaps in care 3. Allowed linkage is between the datasets contained within point (1) above. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS+ and LPF's which contain only secondary care activity 4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG. 5. Aggregated of required data for CCG management use will be completed by Optum Health Solutions (UK) Ltd or the CCG as instructed by the CCG. 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set. Data held by Optum Health Solutions (UK) Ltd for the purpose of the NHS England Wave 2 PHM project will be destroyed within 6 months of the completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.


Project 5 — DARS-NIC-387074-L1X5J

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

Sensitive: Sensitive

When: 2021/01 — 2021/04.

Repeats: One-Off

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

Categories: Anonymised - ICO code compliant

Datasets:

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

Objectives:

NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals. GPES data for pandemic planning and research (GDPPR COVID 19) To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the COVID-19 Directions. The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patient’s GP record, such as details of: • diagnoses and findings • medications and other prescribed items • investigations, tests and results • treatments and outcomes • vaccinations and immunisations Details of any sensitive SNOMED codes included in the GDPPR data set can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data. There are no free text record entries in the data. The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes. Such uses of the data include but are not limited to: • Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact and to estimate when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions. • Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified. • Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions: The data may only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data. The linked data may only be used for purposes stipulated within this agreement and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. Reidentification of individuals is not permitted under this DSA. LEGAL BASIS FOR PROCESSING DATA: Legal Basis for NHS Digital to Disseminate the Data: NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice). The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI. Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes. Legal Basis for Processing: The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2). The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information: Health organisations “Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include: • persons employed or engaged for the purposes of the health service Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population. Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures. Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.

Expected Benefits:

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

Outputs:

• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients due to the impact of COVID-19 • Analysis of resource allocation • Investigating and monitoring the effects of COVID-19 • Patient Stratification in relation to COVID-19, such as: o Patients at highest risk of admission o Frail and elderly o Patients that are currently in hospital o Patients with prescriptions related to COVID-19 o Patients recently Discharged from hospital For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.

Processing:

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


Project 6 — DARS-NIC-216638-L9N4N

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

Sensitive: Sensitive

When: 2018/10 — 2021/04.

Repeats: Frequent Adhoc Flow, One-Off

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

Categories: Anonymised - ICO code compliant

Datasets:

  • SUS for Commissioners

Objectives:

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 geographical region of the CCGs: - NHS Brighton and Hove CCG - NHS Crawley CCG - NHS Horsham and East Sussex CCG HERE is the Prime Contractor for planned MSK Activity above CCG areas. As such, for the duration of the contract, HERE is the commissioner for Planned MSK treatment for patients from the above 3 CCGs. The financial value of this activity is approximately £40m per annum. HERE will produce a report covering planned MSK treatment at all Secondary Care providers. This is business-critical for financial validation, contract management and financial reconciliation between providers (both NHS and Independent), HERE and the CCGs. The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) The pseudonymised data is required to for the following purposes: - Data Quality and Validation - allowing data quality checks on the submitted data - Service redesign - Contract Management - Financial reconciliation 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 South Central and West Commissioning Support Unit and Care Unbound Ltd (trading as HERE) in order to manage the musculoskeletal (MSK) contract for the 3 CCGs.

Expected Benefits:

Effective contractual management and financial reconciliation between CCGs, HERE, NHS Providers and Independent Sector Providers for Planned MSK Care across the CCGs area. South, Central and West Commissioning Support Unit will pass a subset of the pseudonymised data relating to the HERE MSK contract to HERE for the purpose of contract management. The data will be used only for the following purposes: (1) Financial Validation – reconciliation to SUS for the invoices relating to patient activity, that providers charge HERE and CCGs for. (2) Contract Management of subcontracted Providers – including data and activity challenges, within the NHS SUS Timetable. (3) Implementation and monitoring of Clinically Effective Commissioning schemes relating to MSK services. The report will contain the OPCS data contained within SUS, and HERE will use this data to ensure that providers are only carrying out procedures that are deemed of limikted clinical effectiveness when it is clinically appropriate to do so. (4) Clinical Coding Analysis The monthly pseudonymised SUS Data will assist HERE in being able to deliver: • Co-ordinated and integrated care across the MSK pathway as a whole (Orthopaedics, Rheumatology, MSK Pain and non-MSK Pain Management • Reduction in waiting times; • Strategies and processes to reduce incidence of non-attendance (DNAs); • Equity of access to consistent levels of care; • Identification of and reduction in unwarranted variation across the MSK pathway; • Pathways’ efficiencies and the elimination of waste across the entire pathway; • Access to and delivery of diagnostics (MRI, pathology, X-ray, etc) to meet the requirements of One Stop Clinics if appropriate. • Delivery of Clinically Effective Commissioning schemes. • Timely dispute resolution system between Providers and Commissioners (HERE and CCGs) regarding charges for patient activity • Monthly financial reconciliation between CCGs, HERE, NHS and Independent Sector Providers. HERE as Prime Provider will effectively commission sub-contracted Providers to provider planned care.

Outputs:

The expected output is a monthly pseudonymised Patient Level SUS Data report in Microsoft Excel format. The report will provide SUS data relating to activity from the 3 CCG areas for Planned MSK treatment at all Secondary Care providers. This is business-critical for invoice validation, contract management and financial reconciliation between providers (both NHS and Independent), HERE and the CCGs. The report will contain the following details: CCG Code, GP Code, Activity Month, Point of Delivery (POD), Treatment Function Code, Primary Procedure Code (OPCS), Secondary Procedure Code (OPCS) ,Primary Diagnosis Code (ICD10), Secondary Procedure Code (ICD10), Provider Code, Provider Name, Source of Referral Code, Admission Code, Appointment Date, Admission Date, Discharge Date, Length of Stay, HRG Code, Activity Cost, MFF Cost, Excess Days Cost The outputs will also support and enhance general commissioning outputs including: 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 CCGs unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by "Personnel" (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data). Segregation Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. All access to data is audited. 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 commissioner (including historical activity where the patient was previously registered or resident in another commissioner). and/or • Patients treated by a provider where the commissioner 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 purposed and relates to national SUS+ feeds (for the host/co-ordinating commissioner only). and/or • Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the commissioner. For clarity, any access by University Hospital Bristol NHS Foundation Trust to data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. Commissioning The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS+ Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Care Unbound Ltd (trading as HERE) 1) Pseudonymised SUS, only is securely transferred from the DSCRO to South, Central and West Commissioning Support Unit. 2) NHS South, Central and West Commissioning Support Unit add derived fields and then pass the pseudonymised data to Care Unbound Ltd 3) Care Unbound Ltd provide analysis to: a. Conduct financial reconciliation between care providers b. Perform contract management of MSK related activities. 4) Care Unbound Ltd then pass the processed, pseudonymised and linked data to the CCG 5) Aggregation of required data for CCG management use will be completed by Care Unbound Ltd 6) Patient level data will not be shared outside of CCG's and will only be shared within the CCG's 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-169933-S9N9J

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

Sensitive: Sensitive

When: 2018/06 — 2021/04.

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

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

Categories: Anonymised - ICO code compliant

Datasets:

  • Acute-Local Provider Flows
  • Ambulance-Local Provider Flows
  • Children and Young People Health
  • Community Services Data Set
  • Community-Local Provider Flows
  • Demand for Service-Local Provider Flows
  • Diagnostic Imaging Dataset
  • Diagnostic Services-Local Provider Flows
  • Emergency Care-Local Provider Flows
  • Experience, Quality and Outcomes-Local Provider Flows
  • Improving Access to Psychological Therapies Data Set
  • Maternity Services Data Set
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • Mental Health-Local Provider Flows
  • 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
  • Civil Registration - Births
  • Civil Registration - Deaths
  • National Cancer Waiting Times Monitoring DataSet (CWT)
  • National Diabetes Audit
  • Patient Reported Outcome Measures

Objectives:

Commissioning The NHS and local councils have come together in 44 areas covering all of England to develop proposals to improve health and care. They have formed new partnerships – known as sustainability and transformation partnerships – to plan jointly for the next few years. Sustainability and transformation partnerships build on collaborative work that began under the NHS Shared Planning Guidance for 2016/17 – 2020/21, to support implementation of the Five Year Forward View. They are supported by six national health and care bodies: NHS England; NHS Improvement; the Care Quality Commission (CQC); Health Education England (HEE); Public Health England (PHE) and the National Institute for Health and Care Excellence (NICE). The CCG is part of the Sussex and East Surrey Sustainable Transformation Partnership. The STP is responsible for implementing large parts of the 5 year forward view from NHS England. The STP is implementing several initiatives: - Putting the patient at the heart of the health system - Working across organisational boundaries to deliver care and including social care, public Health, providers and GPs as well as CCGs - Reviewing patient pathways to improve patient experience whilst reducing costs e.g. reduce the number of standard tests a patient may have and only have the ones they need - Planning the demand and capacity across the healthcare system across 8 CCGs to ensure we have the right buildings, services and staff to cope with demand whilst reducing the impact on costs - Working to prevent or capture conditions early as they are cheaper to treat - Introduce initiatives to change behaviours e.g. move more care into the community - Patient pathway planning for the above To ensure the patient is at the heart of care, the STP is focussing on where services are required across the geographical region. This assists to ensure delivery of care in the right place for patients who may move and change services across CCGs. The CCG will work proactively and collaboratively with the other CCGs in the STP to redesign services across boundaries to integrate services. Collaborative sharing is required for CCGs to understand these requirements. The CCGs will 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 STP 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 - Ensuring we do what we should - 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 - South, Central and West Commissioning Support Unit

Yielded Benefits:

Commissioning 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities. 14. Reviewing current service provision a. Cost-benefit analysis and service impact assessments to underpin service transformation across health economy b. Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.) c. Impact analysis for different models or productivity measures, efficiency and experience d. Service and pathway review e. Service utilisation review 15. Ensuring compliance with evidence and guidance a. Testing approaches with evidence and compliance with guidance. 16. Monitoring outcomes a. Analysis of variation in outcomes across population group 17. Understanding how services impact across the health economy a. Service evaluation b. Programme reviews c. Analysis of productivity, outcomes, experience, plan, targets and actuals d. Assessing value for money and efficiency gains e. Understanding impact of services on health inequalities 18. Understanding how services impact on the health of the population and patient cohorts a. Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this b. Propensity matching and scoring c. Triple aim analysis 19. Understanding future drivers for change across health economy a. Forecasting health and care needs for population and population cohorts across STPs b. Identifying changes in disease trends and prevalence c. Efficiencies that can be gained from procuring services across wider footprints, from new innovations d. Predictive modelling 20. Delivering services that meet changing needs of population a. Analysis to support policy development b. Ethical and equality impact assessments c. Implementation of NMOC d. What do next years contracts need to include? e. Workforce planning 21. Maximising services and outcomes within financial envelopes across health economy a. What-if analysis b. Cost-benefit analysis c. Health economics analysis d. Scenario planning and modelling e. Investment and disinvestment in services analysis f. Opportunity analysis

Expected Benefits:

Commissioning 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCG outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCG. d. Checking frequent or multiple attendances to improve early intervention and avoid admissions. e. Case management. f. Care service planning. g. Commissioning and performance management. h. List size verification by GP practices. i. Understanding the care of patients in nursing homes. 6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers. 7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these. 8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care. 9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required. 10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework. 11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts 13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities. 14. Reviewing current service provision a. Cost-benefit analysis and service impact assessments to underpin service transformation across health economy b. Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.) c. Impact analysis for different models or productivity measures, efficiency and experience d. Service and pathway review e. Service utilisation review 15. Ensuring compliance with evidence and guidance a. Testing approaches with evidence and compliance with guidance. 16. Monitoring outcomes a. Analysis of variation in outcomes across population group 17. Understanding how services impact across the health economy a. Service evaluation b. Programme reviews c. Analysis of productivity, outcomes, experience, plan, targets and actuals d. Assessing value for money and efficiency gains e. Understanding impact of services on health inequalities 18. Understanding how services impact on the health of the population and patient cohorts a. Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this b. Propensity matching and scoring c. Triple aim analysis 19. Understanding future drivers for change across health economy a. Forecasting health and care needs for population and population cohorts across STPs b. Identifying changes in disease trends and prevalence c. Efficiencies that can be gained from procuring services across wider footprints, from new innovations d. Predictive modelling 20. Delivering services that meet changing needs of population a. Analysis to support policy development b. Ethical and equality impact assessments c. Implementation of NMOC d. What do next years contracts need to include? e. Workforce planning 21. Maximising services and outcomes within financial envelopes across health economy a. What-if analysis b. Cost-benefit analysis c. Health economics analysis d. Scenario planning and modelling e. Investment and disinvestment in services analysis f. Opportunity analysis

Outputs:

Commissioning 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers. 9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11. Contract Management and Modelling 12. Patient Stratification, such as: o Patients at highest risk of admission o Most expensive patients (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community 13. Profiling population health and wider determinants to identify and target those most in need a. Understanding population profile and demographics b. Identify patient cohorts with specific needs or who may benefit from interventions c. Identifying disease prevalence. health and care needs for population cohorts d. Contributing to Joint Strategic Needs Assessment (JSNA) e. Geographical mapping and analysis 14. Identifying and managing preventable and existing conditions a. Identifying types of individuals and population cohorts at risk of non-elective re-admission b. Risk stratification to identify populations suitable for case management c. Risk profiling and predictive modelling d. Risk stratification for planning services for population cohorts e. Identification of disease incidence and diagnosis stratification 15. Reducing health inequalities a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs b. Socio-demographic analysis 16. Managing demand a. Waiting times analysis b. Service demand and supply modelling c. Understanding cross-border and overseas visitor d. Winter planning e. Emergency preparedness, business continuity, recovery and contingency planning 17. Care co-ordination and planning a. Planning packages of care b. Service planning c. Planning care co-ordination 18. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system a. Patient pathway analysis across health and care b. Outcomes & experience analysis c. Analysis to support anti-terror initiatives d. Analysis to identify vulnerable patients with potential safeguarding issues e. Understanding equity of care and unwarranted variation f. Modelling patient flow g. Tracking patient pathways h. Monitoring to support New Models of Care, Accountable Care Organisations and Sustainable Transformation Partnerships i. Identifying duplications in care j. Identifying gaps in care, missed diagnoses and triple fail events k. Analysing individual and aggregated timelines 19. Undertaking budget planning, management and reporting a. Tracking financial performance against plans b. Budget reporting c. Tariff development d. Developing and monitoring capitated budgets e. Developing and monitoring individual-level budgets f. Future budget planning and forecasting g. Paying for care of overseas visitors and cross-border flow 20. Monitoring the value for money a. Service-level costing & comparisons b. Identification of cost pressures c. Cost benefit analysis d. Equity of spend across services and population cohorts e. Finance impact assessment 21. Comparing population groups, peers, national and international best practice a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice b. Benchmarking against other parts of the country c. Identifying unwarranted variations 22. Comparing expected levels a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations 23. Comparing local targets & plan a. Monitoring of local variation in productivity, cost, outcomes, quality and experience b. Local performance dashboards by service provider, commissioner, geography, NMOC, STPs 24. Monitoring activity and cost compliance against contract and agreed plans a. Contract monitoring b. Contract reconciliation and challenge c. Invoice validation 25. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans a. Performance dashboards b. CQUIN reporting c. Clinical audit d. Patient experience surveys e. Demand, supply, outcome & experience analysis f. Monitoring cross-border flows and overseas visitor activity 26. Improving provider data quality a. Coding audit b. Data quality validation and review c. Checking validity of patient identity and commissioner assignment

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. Data cannot be stored in a cloud environment under this agreement. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the Sussex and East Surrey Sustainable Transformation Partnership. No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) Segregation Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. Commissioning The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS 2. Local Provider Flows (received directly from providers) o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening 3. Mental Health Minimum Data Set (MHMDS) 4. Mental Health Learning Disability Data Set (MHLDDS) 5. Mental Health Services Data Set (MHSDS) 6. Maternity Services Data Set (MSDS) 7. Improving Access to Psychological Therapy (IAPT) 8. Child and Young People Health Service (CYPHS) 9. 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 1 - South, Central and West Commissioning Support Unit 1. Pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS) and Diagnostic Imaging data (DIDS) only is held until points 2 – 8 are completed. 2. South, Central and West Commissioning Support Unit receives GP data. GP Data is received as follows: o Identifiable GP data is submitted to South Central and West Commissioning Support Unit. o The identifiable data lands in a ring-fenced area for GP data only. o The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO. o There is a Data Processing Agreement in place between the GP and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the GP. o This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO. o Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted. o South Central and West Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo algorithm specific to them. 3. South, Central and West Commissioning Support Unit also receive a flow of social care data. Social Care data is received in one of the following 2 ways: o Pseudonymised: § Social Care data is pseudonymised within the provider using a pseudonymisation tool, different to that used by the DSCRO. The provider requests a pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the Local Authority and to that specific date. § The pseudonymised data lands in a ring-fenced area for social care data only. § There is a Data Processing Agreement in place between the Provider and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the Provider. § This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO. § The data is then passed into the non-ringfenced area with the pseudo algorithm specific to them. o Identifiable: § Identifiable social care data is submitted to South Central and West Commissioning Support Unit. § The identifiable data lands in a ring-fenced area for social care data only. § The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO. § There is a Data Processing Agreement in place between the Local Authority and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the provider. § This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO. § Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted. § South Central and West Commissioning Support Unit are then sent the pseudonymised social care data with the pseudo algorithm specific to them. 4. Once the pseudonymised GP data and social care data is received, South, Central and West Commissioning Support Unit make a request to the DSCRO. 5. The DSCRO check the dates of the key generation (Point 2d and 3aii/3biv). 6. The DSCRO then send a mapping table to South, Central and West Commissioning Support Unit 7. South, Central and West Commissioning Support Unit then overwrite the organisation specific keys with the DSCRO key. 8. The mapping table is then deleted. 9. The DSCRO pass the pseudonymised SUS, local provider data, Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) securely to South, Central and West Commissioning Support Unit for the addition of derived fields, linkage of data sets and analysis 10. GP and Social care data is then linked to the data sets listed within point 9. 11. South, Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. 12. Aggregation of required data for CCG management use will be completed by South, Central and West Commissioning Support Unit as instructed by the CCG. 13. 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.