NHS Digital Data Release Register - reformatted

NHS Calderdale Ccg

Project 1 — NIC-21942-Y4Q6H

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

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

Benefits:

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

Outputs:

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

Processing:

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

Objectives:

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


Project 2 — NIC-22515-W6S8Y

Opt outs honoured: Y

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

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

Benefits:

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

Outputs:

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

Processing:

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

Objectives:

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


Project 3 — NIC-56504-D8K6T

Opt outs honoured: Y

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

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

Benefits:

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

Outputs:

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

Processing:

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

Objectives:

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


Project 4 — NIC-60454-Q4L6Z

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

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

Benefits:

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

Outputs:

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

Processing:

1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis. 3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG. 4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning: - SUS data and Local Provider data at pseudonymised level - Mental Health (MHSDS, MHLDDS, MHMDS) with SUS - Improving Access to Psychological Therapies (IAPT) with SUS - Diagnostic Imaging Dataset (DIDs) with SUS - Maternity (MSDS) with SUS - Children and Young People’s Health Services (CYPHS) with Local provider data - Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data - Improving Access to Psychological Therapies (IAPT) with Local provider data - Diagnostic Imaging Dataset (DIDs) with Local provider data - Maternity (MSDS) with Local provider data - Children and Young People’s Health Services (CYPHS) with Local provider data 5. eMBED securely transfer pseudonymised outputs for management use by the CCG. 6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 7. Aggregation of required data for CCG management use will be completed by the CSU, eMBED or the CCG as instructed by the CCG. 8. Patient level data will not be shared outside of the CCG (apart from that highlighted in point 9) and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place. 9. The CCG securely transfer Pseudonymised data back to the provider to: a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery; b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider. The Health Informatics Service 1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis. 3. North of England CSU then pass the processed, pseudonymised data to the Health Informatics Service. The Health Informatics Service apply business rules, pricing and create additional categorical fields. No linkage occurs. 4. The Health Informatics Service securely transfer the Pseudonymised data to eMBED to flow directly to the CCG. 5. Aggregation of required data for CCG management use will be completed by the CSU, eMBED or the CCG as instructed by the CCG. 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.

Objectives:

SUS and Local Provider Data - The CCG recognises that good information and intelligence is crucial for the commissioning of high quality and safe services leading to better outcomes for the populations they serve. This application supports this objective. This arrangement was previously agreed to facilitate the transfer of Commissioning Support Services, from Yorkshire & Humber Commissioning Support Unit (Y&H CSU), who previously held ASH status and served the CCGs, to North England CSU (NECS), The Health Informatics Service (THIS) and eMBED Health Consortium, for ongoing provision in line with the NHS England Lead Provider Framework (LPF). Data Processor 1 - NECS is the commissioning support unit working with the CCG. Data Processor 2 - THIS is hosted by Calderdale and Huddersfield Foundation NHS Trust and is a data processor, sub-contracted by NECS, to provide support to the CCG which is an ongoing arrangement The Health Informatics Service ensure the addition of derived fields and the data is processed so that it can be stored in a structured format in secure data warehouses to allow the data to be viewed and interrogated. Data at pseudonymised level is flowed to eMBED and directly to the CCG, by providing secure access to the relevant data warehouses to allow them to view and extract their data, or via secure email or secure file transfer. They provide a very bespoke service to the CCGs they cover, including the following: • Provision of the most up to date hospital submissions so CCG • Frozen contracting views, i.e. in line with PbR timescales and rules for commissioning • Implementation of any local data flows agreed between the CCGs and providers • Supply the CHFT local data feeds which aren’t provided by other data processers • transform the data as required and ensure that the CCG receives a personal and supportive service Data Processor 3 - eMBED was appointed in March 2016 to continue the operations of the Yorkshire and Humber CSU; Kier Business Services Limited, with additional Business Intelligence work carried out under contract by Dr Foster Ltd. Kier Business Services are the prime partner for the LPF within the eMBED Health Consortium. Both organisations (Kier Business Services and Dr Foster Ltd) are a legal entity in their own right. Dr Foster Ltd are subcontracted to Kier Business Services for the delivery of eMBED Health Consortium services. No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.


Project 5 — NIC-83772-T4M1V

Opt outs honoured: N

Sensitive: Sensitive

When: 2017/03 — 2018/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • Local Provider Data - Acute
  • Local Provider Data - Ambulance
  • Local Provider Data - Demand for Service
  • Local Provider Data - Diagnostic Services
  • Local Provider Data - Emergency Care
  • Local Provider Data - Mental Health
  • Local Provider Data - Other not elsewhere classified
  • Local Provider Data - Community
  • SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)

Benefits:

Process 1 The principle benefits to health and/or social care include: • NEEDS - Provide a framework to understand population by need • Patient Benefit – the availability of an integrated dataset will enable the system to design services and new models of care tailored to meet the specific needs of patient cohorts • UTILISATION – summarise the patterns in the use of health and care resources and the associated costs • Patient Benefit – understanding patterns in the use of resources and quantifying its use will allow the system to focus the development of new care models on the needs of the local population, in particular those patients multiple comorbidities who are currently dependent upon episodic unplanned care • PRIORITISATION - Provide the system with a mechanism to prioritise areas for transformation and the introduction of new care models across the health and care system • Patient Benefit – using integrated data sets will enable the identification of patient cohorts with most need and will enable the system to develop the appropriate interventions and models of care that can anticipate and meet patient requirements • BASELINES - Ability to quantify activity and costs to the system, providing baselines and trend analysis • Patients Benefit – provide the system with the capability to demonstrate the impact on reducing the reliance on episodic unplanned care • OUTCOMES – provides baselines to track improvements in health outcomes • Patient Benefit – provide the system with the ability to demonstrate the impact on patients quality of life and their health status as well as the shift from a reliance upon episodic unplanned care to care in the community and closer to home • NEW MODELS OF CARE – provide a vehicle to support integrated approaches to transformation and the capability to monitor the subsequent impact on health outcomes and resource utilisation • Patient Benefit – will support the system to develop non hospital based services so that people can maintain their independence as well as their health and wellbeing • PROVISION – enable clinicians and front line staff to target interventions on specific client groups and provide personalised care • Patient Benefit – enable the system to develop and align an integrated workforce to meet the multiple needs of the local population, in particular high users of unplanned services • NEW PAYMENT MODELS – provide the intelligence to inform the development of new payment models linked to the development of new care models • Patient Benefit – will inform the system to enable funding and investment to follow the needs of patient. The introduction of new payment models will support the shift from the current funding patterns that remunerate activity based payment associated high cost acute care to services that are located in the community and closer to home that recognise and reward improved outcomes Process 2 • Ability to demonstrate the aggregate impact on the public, as a result of the proposed changes outlined in both the RCRTRP and MTC programs. • Benefit to the patient: Consideration of the aggregate capacity issues in relation to the number of beds required across both Trust areas to ensure that the proposed changes provide a system that can deliver improved Quality of Care outcomes (including patient experience) meet patients’ care needs and will result in improved outcomes. • Required to support work with transport providers and patients to: reach agreement on the impact for the public, in terms of potential increased travel time as a result of the proposed changes, for those travelling by Public Transport and private vehicles; understand the Equality implications of these changes; and identify potential mitigations. • Benefit to the patient: People are worried that the impact of additional travelling time will affect their ability to access care and visit people in hospital. This work will enable us to quantify that impact so that we can then work with transport providers, local transport commissioners and patients to consider the impact and how we could address/mitigate the issues in a way that works, taking account of existing public and patient transport, resulting in improved patient experience. • Ability to demonstrate the potential impact on Yorkshire Ambulance service in relation to additional demand and support subsequent commissioning of Ambulance Services • Benefit to the patient: Ensuring that we understand the impact of additional demand/travel time for the Ambulance service ensures that the ambulance service is able to meet this demand and that patient is taken to the correct place to receive care which will ensure access to the correct clinical resources, a better chance of recovery, improved patient experience, improved patient outcomes and a potential impact on mortality. • Aggregate the impact on the flow of patients: attendance, admissions and estimated bed numbers at neighbouring Trusts, particularly Dewsbury District Hospital, Huddersfield Royal Infirmary and Calderdale Royal Hospital. • Benefit to the patient: Understanding the capacity implications of the changes will ensure timely access to care, by clinicians who can meet their needs, resulting in shorter lengths of stay in hospital and improved outcomes for patients • Provide a model to test impact on A&E attendances and Inpatient admissions of both programs. • Benefit to patient: Understanding the changes to the flow of patients as a result of the proposed changes will ensure that access to care does not deteriorate (particularly in relation to wait times for Emergency care and access to timely planned care) resulting in improved outcomes and patient experience and a shorter time in hospital. • As a result of the above, enable the completion of the Full Business Case and Equality and Health Inequality Impact Assessment for the RCRTRP Programme. • Benefit to Patient: Consideration of Equality Issues for patients with protected characteristics enables mitigation to put in place to address these needs. Consideration of Health Inequality issues ensures that potential inequality of access in relation to proposed service changes and current usage by local demographic is identified and mitigation put in place. The overall benefit is to ensure that the proposals would not have any unlawful consequences for people who live or work in our communities • Provide a detailed response to the Joint Health Scrutiny committee on their recommendations regarding the impact on the public and the Yorkshire Ambulance Service. • Benefit to the patient: This is a product of the above requirements and benefits in order to enable independent scrutiny and assurance that the proposed changes are in the best interests of the local health economy.

Outputs:

Process 1 NECS will support Calderdale CCG to undertake a population segmentation exercise of the registered practice population of Calderdale and provide the mechanism to understand range and type of health needs in the population and patterns in the utilisation and cost of health and care resources. Key outputs from the population segmentation exercise will include: • Summary of the population by age and health need • Summary on the utilisation of health and care resources across the population • Framework to identify and prioritise where new care models should be developed • Baseline to understand to track progress overtime – health improvement, utilisation of services, costs associated with activity Process 2 NECS will support Calderdale CCG Right Care, Right Time, Right Place (RCRTRP) & Meeting the Challenge (MTC) programs to undertake patient travel analysis (non-ambulance) and the impact on the public, in terms of potential increased travel time as a result of the proposed changes outlined in both the RCRTRP and MTC programmes. And impact on the flow of patients: attendance, admissions and estimated bed numbers at both DDH and CRH as a result of the proposed changes outlined in both the RCRTRP and MTC programmes. A report will be presented to the Trusts and CCGs outlining the findings of the study, including methodology, calculations and mapping.

Processing:

Process 1 1. North of England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. 2. Data quality management and pseudonymisation of data is completed by the DSCRO using the Open Pseudonymiser tool. The pseudonymised data is then passed securely to North of England CSU BI team for analysis. 3. North of England CSU data team process extracts of GP data sourced from practices across Calderdale and apply the same Open Pseudonymiser algorithm/key to the data as used by the DSCRO. 4. The North of England CSU BI team receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis to support the purpose outlined above. Linkage will take place between, SUS and the GP population extract. 5. Aggregation of required data for CCG management use will be completed by the CSU. 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 where contractual arrangements are in place Process 2 1. North of England Data Services for Commissioners Regional Office (DSCRO) receives flows of local provider data from the Trusts. 2. The DSCRO will derive travel distances and times using the patient postcode submitted by the provider well as postcodes of the hospitals in the area. The output will include a series of derived data items (both travel time and distance) for the different hospitals for each patient record. The postcode will not be output, just the derived times/distances. 3. Data quality management and pseudonymisation of data is completed by the DSCRO. The pseudonymised data is then passed securely to North of England CSU employees within the BI team for analysis. 4. The North of England CSU BI team receives the Pseudonymised data who undertake analysis to support the purpose outlined above. 5. Aggregation of required data for CCG management use will be completed by the CSU. 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 where contractual arrangements are in place.

Objectives:

Process 1 As part of the vision to introduce new care models that can provide care closer to home, it is critical that Calderdale CCG establish an effective framework to identify and prioritise areas that require transformation. This framework will underpin the approach to securing improved health outcomes for the local population from services that can deliver high quality as well as making the best use of resources. To achieve this, NECS will support Calderdale CCG to undertake a population segmentation exercise. The population segmentation exercise will include the total registered population of Calderdale and a framework for commissioners to understand the range and scale of health needs and the patterns in the use of health and care resources. Population segmentation is recognised method to support system transformation. For a comprehensive and robust population exercise to be undertaken, the CCG require pseudonymised SUS data to be linked with GP data. This analysis will enable the health and care system within the Calderdale region to proceed with the development of new models of care and transform the way the system currently operates, providing a greater focus on the prevention of ill health and empowering individuals and communities to maintain their independence and maximise their health and wellbeing. The analysis will also provide a platform for the health and care system to track progress over time and inform the development of new payment mechanisms associated with new models of care being introduced. Process 2 Both the Meeting The Challenge (MTC) and Right Care Right Time Right Place (RCRTRP) have both conducted analyses of the potential impact of reconfiguration on the flow of patients, attendances, admissions and bed numbers of the potential changes to service provision proposed in the respective programmes. This piece of work is to revisit the previous reconfiguration of service provision and model the potential aggregate impact of the two programmes combined. This will include impact on patient flows: attendances, admissions and estimated bed numbers at both Dewsbury and District Hospital (DDH) and Calderdale Royal Hospital (CRH) Outputs from the project will include a report which will be presented to the Trusts and CCGs outlining the findings of the study, including methodology, calculations and mapping.


Project 6 — NIC-90651-Q8W4T

Opt outs honoured: N, Y

Sensitive: Sensitive

When: 2017/03 — 2018/02.

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, 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 - Mental Health
  • Local Provider Data - Other not elsewhere classified
  • Local Provider Data - Population Data
  • Local Provider Data - Primary Care
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  • Maternity Services Dataset

Benefits:

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

Outputs:

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

Processing:

Invoice Validation SUS Data is obtained from the SUS Repository to DSCRO. 1. DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the North of England CSU. 2. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the SUS data flow to validate the corresponding record in the backing data flow b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  3. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Risk Stratification eMBED 1. Identifiable SUS data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to eMBED, who hold the SUS data within eMBED secure storage. 3. Identifiable GP Data is securely sent from the GP system to eMBED. 4. SUS data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS number of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems. 6. eMBED who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication. 7. Once eMBED has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level. Commissioning (Pseudonymised) – SUS and Local Flows eMBED 1. Yorkshire Data Services for Commissioners Regional Office / North England Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire / North of England DSCRO also obtains identifiable local provider data for the CCG directly from Providers. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis. 3. North of England CSU then pass the processed, pseudonymised data to both eMBED and the CCG. 4. eMBED receives the Pseudonymised data for the addition of derived fields, linkage of data sets and analysis. Linked data is limited to the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning: - SUS data and Local Provider data at pseudonymised level - Mental Health (MHSDS, MHLDDS, MHMDS) with SUS - Improving Access to Psychological Therapies (IAPT) with SUS - Diagnostic Imaging Dataset (DIDs) with SUS - Maternity (MSDS) with SUS - Children and Young People’s Health Services (CYPHS) with Local provider data - Mental Health (MHSDS, MHLDDS, MHMDS) with Local provider data - Improving Access to Psychological Therapies (IAPT) with Local provider data - Diagnostic Imaging Dataset (DIDs) with Local provider data - Maternity (MSDS) with Local provider data - Children and Young People’s Health Services (CYPHS) with Local provider data 5. eMBED securely transfer pseudonymised outputs for management use by the CCG. 6. The CCG receive Pseudonymised data from both North of England CSU and eMBED. The CCG then analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 7. Aggregation of required data for CCG management use will be completed by the North of England CSU, eMBED or the CCG as instructed by the CCG. 8. 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. 9. The CCG securely transfer Pseudonymised data back to the provider to: a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery; b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider. The Health Informatics Service 1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields and analysis. 3. North of England CSU then pass the processed, pseudonymised data to the Health Informatics Service. Data will only be processed by substantive employees of the data controller and processors The Health Informatics Service apply business rules, pricing and create additional categorical fields. 4. The Health Informatics Service securely transfer the Pseudonymised data to eMBED to flow directly to the CCG. 5. Aggregation of required data for CCG management use will be completed by the North of England CSU, eMBED or the CCG as instructed by the CCG. 6. 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. Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS 1. North of England Data Services for Commissioners Regional Office (DSCRO) and Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS and MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes. 2. Data quality management, minimisation and pseudonymisation of data is completed by North of England and DSCRO and the pseudonymised data is then passed securely to North of England CSU. 3. North of England CSU then securely transfers the processed, pseudonymised and linked data to eMBED and the CCG. Data will only be processed by substantive employees of the data controller and processors 4. a) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning. b) eMBED receives the data from North of England CSU and carries out further data processing, addition of derived fields, linkage to other data sets and analysis. Linked data includes the following to give a rich and broad clinical journey allowing improved care planning, patient care and commissioning: - Mental Health (MHSDS, MHLDDS, MHMDS) with IAPT - Mental Health (MHSDS, MHLDDS, MHMDS) with SUS - Improving Access to Psychological Therapies (IAPT) with SUS - Diagnostic Imaging Dataset (DIDs) with SUS - Maternity (MSDS) with SUS - Children and Young People’s Health Services (CYPHS) with SUS 5. Aggregation of required data for CCG management use is completed by the CSU or the CCG as instructed by the CCG. 6. 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.

Objectives:

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