NHS Digital Data Release Register - reformatted

NHS Brent CCG

Project 1 — DARS-NIC-160958-K3J4W

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

Sensitive: Sensitive

When: 2018/06 — 2019/01.

Repeats: Frequent adhoc flow, Frequent Adhoc Flow

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

Categories: Anonymised - ICO code compliant

Datasets:

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

Objectives:

Commissioning To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the 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 CCG is part of the North West London 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: 1. Putting the patient at the heart of the health system 2. Working across organisational boundaries to deliver care and including social care, public Health, providers and GPs as well as CCGs 3. 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 4. Planning the demand and capacity across the healthcare system across 7 CCGs to ensure we have the right buildings, services and staff to cope with demand whilst reducing the impact on costs 5. Working to prevent or capture conditions early as they are cheaper to treat 6. Introduce initiatives to change behaviours e.g. move more care into the community 7. 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 following CCGs are Joint Data Controllers and will receive data for the area of residence and registration for the CCGs listed: - NHS Brent CCG - NHS Central London CCG - NHS Ealing CCG - NHS Hammersmith and Fulham CCG - NHS Harrow CCG - NHS Hillingdon CCG - NHS Hounslow CCG - NHS West London CCG The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) - Local Provider Flows o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Diagnostic Imaging Data Set (DIDS) The pseudonymised data is required to 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 North East London Commissioning Support Unit and NHS Brent CCG

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: a. Patients at highest risk of admission b. Most expensive patients (top 15%) c. Frail and elderly d. Patients that are currently in hospital e. Patients with most referrals to secondary care f. Patients with most emergency activity g. Patients with most expensive prescriptions h. Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community 13. 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 14. 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 15. 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 16. Care co-ordination and planning a. Planning packages of care b. Service planning c. Planning care co-ordination 17. 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 18. 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 19. 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 20. 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 21. Comparing expected levels a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations 22. 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 23. Monitoring activity and cost compliance against contract and agreed plans a. Contract monitoring b. Contract reconciliation and challenge c. Invoice validation 24. 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 25. 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. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the North West London 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 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 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. Diagnostic Imaging Data Set (DIDS) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 – North East London Commissioning Support Unit 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North East London Commissioning Support Unit. 2. North East London Commissioning Support Unit land the data only. No processing or analysis occurs. North East London Commissioning Support Unit then securely transfer the data to NHS Brent CCG. 3. NHS Brent CCG link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning. b. Check recorded activity against contracts or invoices and facilitate discussions with providers. c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 4. Allowed linkage is between the data sets contained within point 1. 5. NHS Brent CCG then pass the processed, pseudonymised and linked data to the CCG. 6. Aggregation of required data for CCG management use will be completed by NHS Brent CCG or the CCG as instructed by the CCG. 7. 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 2 — DARS-NIC-86054-Q4Y8W

Opt outs honoured: Yes - patient objections upheld (Section 251)

Sensitive: Sensitive

When: 2018/06 — 2019/01.

Repeats: Frequent adhoc flow, Frequent Adhoc Flow

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 NHS Brent CCG The CCG are advised by Brent CCG CEfF 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 NHS Brent CCG

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. 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 by the Data Services for Commissioners Regional Office (DSCRO). 2. The DSCRO pushes a one-way data flow of SUS+ data to North East London CSU who land the data only. 3. North East London CSU then securely transfer the data directly into the Controlled Environment for Finance (CEfF) located in the CCG. 4. The CEfF conduct the following processing activities 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. In relation to a patient registered with the CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  5. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved. 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 CSU for landing only. 3. North East London CSU then securely transfer the data to the CCG, who hold the SUS data within the secure Data Centre on N3. 4. Identifiable GP Data is securely sent from the GP system to the CCG. 5. SUS+ data is linked to GP data in the risk stratification tool by the data processor. 6. 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. 7. The CCG 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. 8. Once the CCG has completed the processing, access is available through the online system via a secure N3 connection to access the data pseudonymised aggregate with small number suppression .


Project 3 — NIC-43419-N9K7N

Opt outs honoured: Y, N

Sensitive: Sensitive

When: 2016/12 — 2017/02.

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

Objectives:

ASH Status This is an application to use SUS data identifiable at the level of NHS Number and local provider data identifiable at the level of NHS Number according to S.251 CAG 2-03(a)/2013. The NHS number 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 analysis of patient data across health pathways. The application also includes a request for MHSDS, MHMDS, MHLDDS and MSDS data identifiable at the level of NHS number to provide intelligence to support commissioning of health services. 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 This is an application for the CCG to use pseudonymised SUS and local provider data to provide intelligence to support commissioning of health services. The linked, pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. Pseudonymised – IAPT, CYPHS and DIDS This is an application for the CCG to use 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 the HSCIC will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

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

Outputs:

ASH Status 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. 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. ASH – 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 – IAPT, CYPHS and DIDS 1) Commissioner reporting: (a) Summary by provider view - plan & actuals year to date (YTD). (b) Summary by Patient Outcome Data (POD) view - plan & actuals YTD. (c) Summary by provider view - activity & finance variance by POD. (d) Planned care by provider view - activity & finance plan & actuals YTD. (e) Planned care by POD view - activity plan & actuals YTD. (f) Provider reporting. (g) Statutory returns. (h) Statutory returns - monthly activity return. (i) Statutory returns - quarterly activity return. (j) Delayed discharges. (k) Quality & performance referral to treatment reporting. 2) Readmissions analysis. 3) Production of aggregate reports for CCG Business Intelligence. 4) Production of project / programme level dashboards. 5) Monitoring of acute / community / mental health quality matrix. 6) Clinical coding reviews / audits. 7) Budget reporting down to individual GP Practice level.

Processing:

South London DSCRO will apply Type 2 objections (from 1st October 2016 onwards) before any identifiable data leaves the DSCRO. ASH Status For the purpose of commissioning activities, the CCG requires SUS data identifiable at the level of NHS Number. The CCG also requires local provider data identifiable at the level of NHS number. South East CSU acts as the data processor on behalf of the CCG, receiving SUS and local provider data identifiable at the level of NHS number. South London DSCRO has a legitimate relationship with the CCG, for the provision of data. 1. a) South London DSCRO– part of the HSCIC - receive identifiable SUS data from the SUS Repository at HSCIC. DSCRO also receives identifiable local provider data directly from Providers (as per Data Services for Commissioners Directions 2015). b) South London DSCRO also receives MHMDS, MHSDS, MHLDDS and MSDS data with NHS number. 2. Data quality management and standardisation of the data is completed by South London DSCRO. 3. a) South London DSCRO then securely transfers the SUS data identifiable at the level of NHS number and Local Provider data identifiable at the level of NHS number to South East CSU. 4. South London DSCRO then securely transfers the MHMDS, MHSDS, MHLDDS and MSDS data identifiable at the level of NHS number to South East CSU. 5. South East CSU ensures the addition of derived fields and analysis takes place, including linkage of SUS and local provider data, then flows the data securely to the CCG. Risk Stratification 1) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from South London Data Services for Commissioners Regional Office (DSCRO) to the data processor. 2) Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to South East CSU, who hold the SUS data within the secure Data Centre on N3. 3) SUS data is linked to GP data in the risk stratification tool by the data processor. 4) As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 5) 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. 6) Once South East CSU has completed the processing, the CCG can dial into the online system via N3 connection to access the data anonymised at patient level. Pseudonymised – IAPT, CYPHS and DIDS 1) South London Data Services for Commissioners Regional Office (DSCRO) receive a flow of pseudonymised patient level data for each CCG for Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes 2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to South East CSU for the addition of derived fields and analysis. 3) South East CSU then pass the processed, pseudonymised data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning 5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level. 6) Patient level data will not be shared outside of the CCG 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.


Project 4 — NIC-86054-Q4Y8W

Opt outs honoured: N, Y

Sensitive: Sensitive

When: 2017/03 — 2018/05.

Repeats: Ongoing

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

Categories: Anonymised - ICO code compliant, Identifiable

Datasets:

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

Objectives:

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

Expected Benefits:

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

Outputs:

Invoice Validation 1. Addressing poor data quality issues 2. Production of reports for business intelligence 3. Budget reporting 4. Validation of invoices for non-contracted events Risk Stratification 1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. 3. Record level output will be available for commissioners (of the CCG), pseudonymised aggregate with small number suppression 4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient. 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: 6. Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost 7. Plan work for commissioning services and contracts 8. Set up capitated budgets 9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes. Commissioning (Pseudonymised) – SUS and Local Flows 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals 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. Commissioning (Pseudonymised) – Mental Health, Maternity, IAPT, CYPHS and DIDS 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers.

Processing:

The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO. The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those substantive employees with authorised user accounts used for identification and authentication. Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. Any identifiable data previously received from NHS Digital for the purpose of commissioning has been destroyed, not just SUS data. Invoice Validation 1. SUS Data is obtained from the SUS Repository by the Data Services for Commissioners Regional Office (DSCRO). 2. The DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) located in the CCG. 3. The CEfF conduct the following processing activities for invoice validation purposes: 4. Checking the individual is registered to the Clinical Commissioning Group (CCG) by using the derived commissioner field in SUS and associated with an invoice from the SUS data flow to validate the corresponding record in the backing data flow 5. 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: 6. In line with Payment by Results tariffs 7. In relation to a patient registered with the CCG GP or resident within the CCG area. 8. The health care provided should be paid by the CCG in line with CCG guidance.  9. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved 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 the CCG, who hold the SUS data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to the CCG. 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. The CCG 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 the CCG has completed the processing, access is available through the online system via a secure N3 connection to access the data pseudonymised aggregate with small number suppression Commissioning (Pseudonymised) – SUS and Local Flows 1. The Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. The DSCRO also obtains identifiable local provider data for the CCG directly from Providers. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows. 3. North East London 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 can be shared. Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS 1. The 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 the DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields and analysis. 3. North East London 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 disclosure control applied can be shared.