NHS Digital Data Release Register - reformatted

NHS Scarborough and Ryedale CCG

Project 1 — DARS-NIC-90691-W4B6F

Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld (Section 251)

Sensitive: Sensitive

When: 2018/06 — 2019/03.

Repeats: Frequent adhoc flow, Frequent Adhoc Flow

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'.

Categories: Anonymised - ICO code compliant, Identifiable

Datasets:

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

Objectives:

Invoice Validation Invoice validation is part of a process by which providers of care or services get paid for the work they do. Invoices are submitted to the Clinical Commissioning Group (CCG) so they are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets and will not be used further. The legal basis for this to occur is under Section 251 of NHS Act 2006. Invoice Validation with be conducted by North of England CSU The CCG are advised by North of England CSU whether payment for invoices can be made or not. Risk Stratification Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes. To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care. The legal basis for this to occur is under Section 251 of NHS Act 2006 (CAG 7-04(a)). Risk Stratification will be conducted by eMBED Commissioning To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) - Local Provider Flows o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Diagnostic Imaging Data Set (DIDS) The pseudonymised data is required to for the following purposes: § Population health management: • Understanding the interdependency of care services • Targeting care more effectively • Using value as the redesign principle § Data Quality and Validation – allowing data quality checks on the submitted data § Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them § Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs § Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated § Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another § Service redesign § Health Needs Assessment – identification of underlying disease prevalence within the local population § Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. Processing for commissioning will be conducted by North of England CSU, Scarborough and Ryedale CCG (Partnership Commissioning Unit) & eMBED

Expected Benefits:

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

Outputs:

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

Processing:

Data must only be used as stipulated within this Data Sharing Agreement. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG. Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. All access to data is managed under Roles-Based Access Controls No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data for the purpose of risk stratification leaves the DSCRO. CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools. Segregation Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors. Invoice Validation 1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the North of England CSU. 3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data. b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between North of England 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 On 20th July 2017, North of England CSU ceased to deliver risk stratification. eMBED is the sole Data Processor for Risk Stratification. 1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to eMBED ,who hold the SUS+ data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to eMBED. 4. SUS+ data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 6. Once eMBED has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level. Commissioning The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS+ 2. Local Provider Flows (received directly from providers) a. Acute b. Ambulance c. Community d. Demand for Service e. Diagnostic Service f. Emergency Care g. Experience, Quality and Outcomes h. Mental Health i. Other Not Elsewhere Classified j. Population Data k. Primary Care Services l. Public Health Screening 3. Mental Health Minimum Data Set (MHMDS) 4. Mental Health Learning Disability Data Set (MHLDDS) 5. Mental Health Services Data Set (MHSDS) 6. Maternity Services Data Set (MSDS) 7. Improving Access to Psychological Therapy (IAPT) 8. Child and Young People Health Service (CYPHS) 9. Diagnostic Imaging Data Set (DIDS) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 and 2 – North of England Commissioning Support Unit and eMBED Health Consortium 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North of England Commissioning Support Unit. 2. North of England Commissioning Support Unit then pass the processed, pseudonymised data to both eMBED Health Consortium and the CCG. 3. eMBED Health Consortium add derived fields, link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning. b. Check recorded activity against contracts or invoices and facilitate discussions with providers. c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 4. Allowed linkage is between the data sets contained within point 1. 5. eMBED Health Consortium then pass the processed, pseudonymised and linked data to the CCG. 6. The CCG analyse the data received from eMBED Health Consortium and North of England Commissioning Support Unit 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 North of England Commissioning Support Unit, eMBED Health Consortium or the CCG as instructed by the CCG. 8. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set. 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. Data Processor 3 –Scarborough and Ryedale CCG Partnership Commissioning Unit 1. North of England and Yorkshire Data Services for Commissioners Regional Office (DSCRO) receives 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) for commissioning purposes and only is securely transferred from the DSCRO to North of England CSU 2. North of England CSU add derived fields, link data and provide analysis to: a. See patient journeys for pathways or service design, re-design and de-commissioning. b. Check recorded activity against contracts or invoices and facilitate discussions with providers. c. Undertake population health management d. Undertake data quality and validation checks e. Thoroughly investigate the needs of the population f. Understand cohorts of residents who are at risk g. Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contained within point 1. 4. North of England CSU then pass the processed, pseudonymised and linked data to the Partnership Commissioning Unit (PCU), hosted by Scarborough and Ryedale CCG. 5. The PCU utilises the data for monitoring for the CCGs supported by the PCU against their contracts and national standards. They also monitor the provider data against NHS England reports and NHS Digital data to be able to, challenge and areas of issue/mistake by using the data sets and monitor data quality. Analysis is provided on lower level practice reporting and monitoring, age profiling, early intervention reporting, and unify submission commissioner return, seven day follow ups and crisis gate keeping. There is no linkage with SUS data other what is stated above within the application which takes place to give a complete patient pathway analysis. Only substantive employees have access to the data. 6. Aggregation of required data for CCG management use will be completed by North of England CSU 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 — NIC-21865-P5N6D

Opt outs honoured: N

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

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

Objectives:

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

Expected Benefits:

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

Outputs:

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

Processing:

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


Project 3 — NIC-36253-D9W8D

Opt outs honoured: Y

Sensitive: Sensitive

When: 2016/12 — 2017/02.

Repeats: Ongoing

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

Categories: Identifiable

Datasets:

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

Objectives:

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

Expected Benefits:

Risk Stratification promotes improved case management in primary care which is expected to lead to the following benefits being realised : 1. Improved planning by better understanding the patient flows through the healthcare system, thus allowing GPs and clinicians to design appropriate pathways to improve patient flow and identify plans to address these. 2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved via the mapping of frequent users of emergency services and the 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 reduce premature mortality by more targeted intervention in primary care, which supports the commissioner to meet its requirement to reduce premature mortality in line with the CCG Outcome Framework. It is expected that all of the aforementioned will lead to improved patient experience through more effective direct patient care services.

Outputs:

To provide risk profiling, calculated on activity data from secondary, urgent and primary care. As part of the risk stratification processing activity detailed above, the GP practice has access to the RAIDR tool for reports which present to them their registered patients and associated risk score. The only identifier to be provided to the GP practice is the NHS number of their registered patient (for their own patients only). The GP practice can access the RAIDR tool, which is a secure portal, at any time which will support MDT (multi-disciplinary team) discussions around ongoing patient care. The GP practice can copy and paste the NHS number presented in the secure web-portal to any other program including the practice clinical system. CCG staff who have been granted access to the RAIDR tool can only access aggregate output / reports. No record-level SUS is provided to any other organisation.

Processing:

Processing of SUS Data for the purposes of Risk Stratification includes landing, processing, staging and publication. 1. Landing A local flow of identifiable urgent care data is submitted from healthcare providers to DSCRO North of England. DSCRO North of England transfer the local provider urgent care data identifiable at the level of NHS number to NECS using a secure file transfer process and the urgent care data is landed in secure NECS network storage. Prior to the release of SUS data by DSCRO North England, Type 2 objections will be applied and the relevant patients data redacted. DSCRO North of England securely transfer SUS data identifiable at the level of NHS number to North of England Commissioning Support Unit (NECS). This is done by landing the SUS data in secure NECS network storage. Data is landed and processed in an access restricted server at NECS. Primary care data identifiable at the level of NHS number is extracted from GP clinical systems and downloaded to secure NECS network storage – all patient objections are handled at the point of data extraction with no identifiable data flowing where patients have a relevant dissent code (these include both type 1 and 2 as well as local system codes). Only named individuals have access to process the data. All users undertake regular IG training, in line with IGT requirements. 2. Processing (ETL) Data is processed on a monthly basis, which follows NECS ETL (Extract, Transform and Load) process as follows. 2.1. Cleaning and quality checks are carried out on the data. 2.2. The primary care, and SUS & urgent care local provider data are combined using NHS number to link the data and the data is processed to create a risk stratification data set 2.3. The urgent care data is linked to primary care data to calculate a risk score for each admission/attendance. 3. Staging Data is landed to a secure NECS staging area for final quality checks. 4. Publication Outputs are available to the CCG and the GP practice via the RAIDR tool which has a secure web-portal for accessing the data. All usage of its tools is audited. Access to the RAIDR tool is via individual usernames and passwords. Data identifiable at the level of NHS number is only available to named individuals within the GP practice who have a legitimate relationship with the patient or where an individual working within a GP practice has the authorisation of a senior individual - such as senior partner or business manager within the practice - to access data identifiable at the level of NHS number for the purposes of conducting Risk Stratification for case finding. This is only applies where there is a legitimate relationship with the patient for direct patient care. (For example, staff such as community/practice nurses who work as part of a multi-disciplinary team with the GPs.) The CCG has an aggregated view only of Risk Stratification data based on their related GP practices. No record-level SUS data identifiable at the level of NHS number is provided to any other organisation.


Project 4 — NIC-60449-S4F7K

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

Objectives:

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

Expected Benefits:

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

Outputs:

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

Processing:

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


Project 5 — NIC-90691-W4B6F

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:

  • 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
  • Children and Young People's Health Services Data Set
  • Improving Access to Psychological Therapies Data Set
  • Maternity Services Dataset
  • SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)

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.

Expected Benefits:

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

Outputs:

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

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 Data Processor 1 - North England CSU 1. Identifiable SUS data is obtained from the SUS Repository to Yorkshire Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management and standardisation of data is completed by DSCRO and the data identifiable at the level of NHS number is transferred securely to North of England CSU, who hold the SUS data within the secure NECS network storage. 3. Identifiable GP Data is securely sent from the GP system to North of England CSU. 4. SUS data is linked to GP data in the risk stratification tool by the data processor. 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier derived from SUS available to GPs is the NHS numbers of their own patients. Any further identification of the patients is derived from the GP data sourced from their own systems. 6. North of England CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication. 7. Once North of England CSU has completed the processing, the CCG can access the online system via a secure network connection to access the data pseudonymised at patient level. On or before 20th July 2017, this data processor will cease to deliver risks stratification, at which point a data destruction certificate will be completed. eMBED will the sole Data Processor for Risk Stratification. eMBED will run adjacently to NECS until NECS ceases. Data Processor 2 - 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 Data Processor 2 - 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. 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 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. 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. Data Processor 3 –Scarborough and Ryedale CCG (Partnership Commissioning Unit) 1. North of England and Yorkshire Data Services for Commissioners Regional Office (DSCRO) receives 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) for commissioning purposes. 2. Data quality management and pseudonymisation of data is completed by DSCRO and the pseudonymised data is then passed securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis. 3. North of England CSU then passes the processed, pseudonymised and linked data to the Partnership Commissioning Unit (PCU), hosted by Scarborough and Ryedale CCG. 4. The PCU utilises the data for monitoring for the CCGs supported by the PCU against their contracts and national standards. They also monitor the provider data against NHS England reports and NHS Digital data to be able to, challenge and areas of issue/mistake by using the data sets and monitor data quality. Analysis is provided on lower level practice reporting and monitoring, age profiling, early intervention reporting, and unify submission commissioner return, seven day follow ups and crisis gate keeping. There is no linkage with SUS data other what is stated above within the application which takes place to give a complete patient pathway analysis. Only substantive employees have access to the data. 5. Aggregated reports only with small number suppression in line with the HES analysis guide are shared with the CCG from the PCU.