NHS Digital Data Release Register - reformatted

NHS Brighton And Hove Ccg

Project 1 — 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

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.

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


Project 2 — 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

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.

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.