NHS Digital Data Release Register - reformatted

NHS North Kirklees Ccg

Project 1 — NIC-159523-F1C1P

Opt outs honoured: N

Sensitive: Sensitive

When: 2018/03 — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • SUS for Commissioners

Benefits:

1. Improved performance against national Better Care Fund metrics 2. Reduction in A&E attendances (especially for elderly persons) 3. Reduction in emergency hospital admissions (especially for elderly persons) 4. Accurate evaluation of local Better Care Fund schemes 5. Accurate evaluation of system transformation of Intermediate Care 6. Improved experience of service users 7. Improved health outcomes 8. Improved social care outcomes 9. Improved productivity thorough streamlining and integration of services.

Outputs:

Reports, analyses and dashboards to support the integration of health and social care including: 1. Falls 2. Better Care Fund national metrics 3. Better Care Fund local schemes 4. Intermediate Care

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 North Kirklees CCG and Greater Huddersfield CCG. Patient level data will not be shared outside of the Local Authority unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data. No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) Segregation Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. All access to data is audited The Data Services for Commissioners Regional Office (DSCRO) obtains the following data set: 1. SUS+ Data quality management and pseudonymisation is completed within the DSCRO using the Nottingham Open Pseudonymiser tool and is then disseminated as follows: Data Processor – PI Limited 1) Pseudonymised SUS+ is securely transferred from the DSCRO to PI Limited. 2) Kirklees Metropolitan Council pseudonymise social care data using the Nottingham Open Pseudonymiser tool. 3) Kirklees Metropolitan Council then securely transfer the pseudonymised social care data to PI Limited. 4) PI Ltd link the SUS+ data and Social Care and load the data into the CareTrak Business Intelligence Tool 5) Data will only be shared within the Council on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

Objectives:

The purpose of this data flow is to enable the Integrated Commissioning Exec –ICE (Kirklees Council, NHS North Kirklees CCG and NHS Greater Huddersfield CCG) to understand how services, and the trajectory of service users interact around social care provision and hospital utilisation (by linking pseudonymised social care data with pseudonymised SUS data).


Project 2 — NIC-21953-L9X5L

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 3 — NIC-22537-H4J9R

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:

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 and primary care. As part of the risk stratification processing activity detailed above, the GP practice has access to the secure web-portal for reports which present to them their registered patients and associated risk score. The GP practice can access the secure web-portal at any time to support MDT (multi-disciplinary team) discussions around ongoing patient care, and enhanced service requirements. 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. There are two views of the data available, pseudonymised and identifiable at the level of NHS number. The data identifiable at the level of NHS number is only available to the GP practice who has a legitimate relationship with the patient. GP practice access to the data is authorised by the GP practice Caldicott Guardians. The CCG can access a pseudonymised view of the data only. 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 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 SUS and (Mental Health and Community) local provider data identifiable at the level of NHS number to NECS. This is done by landing the SUS and local provider data in secure NECS network storage. Primary care data extracts from GP clinical systems identifiable at the level of NHS number are downloaded and transferred to NECS by landing the data in secure NECS network storage. Only named individuals have access to process the data. All users undertake regular IG training, in line with IGT requirements. 2. Processing Data is processed on a monthly basis. 2.1 Primary care data is checked for codes relating to Type 1 patient objections and sensitive conditions to provide assurance that there is no data included where these codes exist, prior to processing of the data. 2.2 Cleaning and quality checks are carried out on the primary care data. 2.3 The primary care is then combined with the SUS and (Mental Health and Community) local provider data using NHS numbers to link the data. 2.4 The combined dataset is processed to produce the calculated risk scores for each patient. 3. Staging Data is landed to a secure NECS staging area for final quality checks before the data is loaded for publication. 4. Publication The data is loaded and published using the NECS SQL BI stack, which includes storage of the data in the NECS secure network storage and a secure web-portal for making the data available to GP practices. 4.1. GP practice access to data (for their own patients only): Data identifiable at the level of NHS number is presented via the secure web-portal to the GP practice who has a legitimate relationship with the patient. 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. The web-portal is accessed by the GP practice using a username and password. The GP practice has access to SUS data identifiable at the level of NHS number to see aspects of the inpatient and outpatient activity via the secure web-portal. All usage of the secure web-portal is audited and access rights are granted by the Caldicott Guardians at the GP practice. 4.2. CCG access to data: The CCG can access a pseudonymised view of the data only.

Objectives:

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


Project 4 — NIC-60470-V4B7X

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 12. “Deep dive” analysis of hospital activity at aggregate level. 13. Cross CCG benchmarking at aggregate level. 14. Provision of aggregate activity data to CCGs’ stakeholders e.g. Health and Wellbeing Boards where the CCG have agreed to this. PI Benchmark Access to the data is provided to the CCG and Local Authority only, and will only be used for the health purposes outlined above. The data will only be processed by Local Authority employees in fulfilment of their public health function, and will not be transferred, shared, or otherwise made available to any third party, including any organisations processing data on behalf of the Local Authority or in connection with their legal function [except for the CCG named in this application]. Such organisations may include Commissioning Support Units, Data Services for Commissioners Regional Offices, any organisation for the purposes of health research, or any Business Intelligence company providing analysis and intelligence services (whether under formal contract or not).

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 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 only relating to the original provider, back to the provider: 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 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. 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. PI Limited (PI Care and Health) 1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) receive a flow of identifiable SUS data for North Kirklees CCG and Greater Huddersfield CCG from SUS. 2. Data quality management of data is completed by the DSCRO. The SUS data is then pseudonymised using University of Nottingham open pseudonymiser tool - a standalone windows desktop application which creates a digest of one or more columns of a CSV file, using a shared key (SALT file) • NHS Number will be fully pseudonymised at source with no organisation that has access to the data having access to the key • Date of Birth will be substituted at source for age at assessment. • Postcode will be substituted at source for lower layer super output area (LSOA) code. 3. The completed pseudonymised file is then passed to PI Limited (PI Care and Health) via secure FTP. 4. Data quality management of social care data is completed by Kirklees Council. The social care data is then pseudonymised using University of Nottingham open pseudonymiser tool. Pseudonymised Social Care Data will be sent to PI Limited (PI Care and Health) direct from the Data Controller (Kirklees Council) via secure FTP. 5. PI Limited (PI Care and Health) then link the data using the common pseudo link, which is undertaken within a controlled environment by a named member of staff, then produce online reports using CareTrak data analysis tool to provide Kirklees Council and the CCG with a range of high level commissioning intelligence based on integrated pathways of care in Kirklees. Access to these reports is based on user access controls, as follows: a) Access to the commissioning intelligence at pseudonymised level is accessible by 2 named members of staff in the Council and 2 named CCG staff (based on a super user access licence for CareTrak) b) Access to aggregate commissioning intelligence (anonymised) is available to up to 3 additional users across the Council and the CCG (standard user licence) Access to the CareTrak system, both on a super user and standard user approach is governed via respective organisation employee code of practice, data protection policies and information governance protocols. Additionally, super users conform to a specific information access agreement which mitigates the risk of how the pseudo data can be handled and used. The pseudonymised data provided back to Kirklees Council will be stored separately to the original identifiable data and the organisation will not attempt to combine these datasets or re-identify the data. 6. The Kirklees Partnership will use this to analytically understand patient journeys for pathway or service design. Data Processing Agreements are in place between Kirklees Council, North Kirklees CCG and PI Limited (PI Care and Health). The pseudonymisation key will not be received by PI Limited (PI Care and Health) from either the DSCRO or Kirklees Council. Pseudonymisation that allows data to be matched is dependent on having the correct key. The key will only be shared by the DSCRO with 4 specified individuals in Kirklees Council (to cover absence or change of position). Staff within the Business Support Unit of Kirklees Council are contractually bound by the policies and procedures set in place to ensure safe and robust management and analysis of sensitive confidential and identifiable data for and on behalf of the population of Kirklees. Four named individuals working with this team will have the documented responsibility to, if required, use the key provided by the DSCRO to ensure that data to be linked, as agreed by the Integrated Commissioning Exec (a partnership between Directors of Kirklees Council, NHS North Kirklees CCG and NHS Greater Huddersfield CCG) is pseudonymised using the Nottingham Open Pseudonymiser and that same key. Neither DSCRO nor Kirklees Council will share the key with PI Limited (PI Care and Health). The key cannot be used to re-identify data as the tool does not allow for this to happen, it only allows for one way pseudonymisation.

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 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) 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. Data Processor 4 – PI Limited (PI Care and Health) To support the Kirklees vision for integrated health and social care (Kirklees 2020) and to ensure the CCG meet the ambition of the Care Act, the Children and Families Act and the Kirklees Better Care Fund along with established legislation, it is crucial that North Kirklees CCG and Greater Huddersfield CCG develops a set of ‘enablers’ to shift from the current, sometimes fragmented, models of care to a more coherent model. One of these ‘enablers’ is to have in place a robust approach to integrated informatics, which includes ways of integrating health and social care data. Data is a vital asset, both for the provision of services and for the efficient management of services and resources. It is therefore essential that the data the CCG hold is intelligently analysed and leveraged to inform strategic commissioning decisions, assist with the evaluation of project outcomes and to enable a culture of shared decision making across the care system. In order for the CCG to provide a range of commissioning intelligence that is linked to local partnership priorities and to support the approach to measuring activity, outcome and financial impact of local Better Care Fund schemes and other jointly commissioned care pathways, the CCG require pseudonymised SUS data to be linked with social care data via their contracted data processor – PI Limited (PI Care and Health)*. *PI Care and Health is a product of the company PI Limited. PI Limited also known as PI Benchmark. The company registration number is 1728605. 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-90698-W7X6Y

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

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:

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) – SUS and Local Flows Data Processor 4 PI Benchmark The Integrated Commissioning Executive for Kirklees (which includes the local authority and both NHS Greater Huddersfield CCG and NHS North Kirklees CCG) wanted to better appreciate the potential and impact of how Better Care Fund monies were being utilised, and whether there were more effective ways to analyse or target the work. PI Care and Health were selected for this work based on their existing work in this field, their clarity in defining the detail of what could be done and how, their engagement and attitude, ability to deliver and price. 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:

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 is derived from the GP data sourced from 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 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. 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 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 CCG Business Intelligence - Production of project / programme level dashboards - Monitoring of acute / community services - Budget reporting

Processing:

Risk Stratification On or before 20th July 2017, one of these data processors will be instructed to cease delivery of risk stratification, at which point a data destruction certificate will also be requested from that data processor. Notification will be made in writing to both Data Processors of the decision to cease or continue service, NHS Digital will sent a copy The data destruction certificate will also be shared with NHS Digital. From the 21st of July 2017 there will be only one Data Processor for Risk Stratification for North Kirklees. eMBED and NECS will run adjacently to one another until the 20th of July 2017 or until notified A data destruction certificate for the previous risk stratification data processor will be provided Data Processor 1 North England CSU (NECS) 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. 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. 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. 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 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. 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. 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. Data Processor 4 PI Benchmark 1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) receive a flow of identifiable SUS data for North Kirklees CCG from SUS. 2. Data quality management of data is completed by the DSCRO. The SUS data is then pseudonymised using University of Nottingham open pseudonymiser tool - a standalone windows desktop application which creates a digest of one or more columns of a CSV file, using a shared key (SALT file) controlled by Yorkshire Data Services for Commissioners Regional Office 3. The completed pseudonymised file is then passed to PI Limited (PI Care and Health) via secure FTP. 4. Data quality management of social care data is completed by Kirklees Council. The social care data is then pseudonymised using University of Nottingham open pseudonymiser tool. Pseudonymised Social Care Data will be sent to PI Limited (PI Care and Health) direct from Kirklees Council via secure FTP. 5. The pseudonymisation key cannot be used to re-identify data as the tool does not allow for this to happen, it only allows for one way pseudonymisation. 6. PI Limited (PI Care and Health) then link the data using the common pseudo link, which is undertaken within a controlled environment by a named member of staff, who then produce online reports using CareTrak data analysis tool to provide North Kirklees CCG, CCG with a range of high level commissioning intelligence based on integrated pathways of care in Kirklees. Access to these reports is based on user access controls, as follows: - Access to the commissioning intelligence at pseudonymised level is accessible by 2 named members of staff in the CCG (based on a super user access licence for CareTrak) - Access to aggregate commissioning intelligence (anonymised) is available to up to 3 additional users across the CCG (standard user licence) - External aggregated reports only with small number suppression can be shared. Access to the CareTrak system, both on a super user and standard user approach is governed via respective organisation employee code of practice, data protection policies and information governance protocols. Additionally, super users conform to a specific information access agreement which mitigates the risk of how the pseudo data can be handled and used. The Integrated Commissioning Executive for Kirklees (which includes the local authority and both NHS Greater Huddersfield CCG and NHS North Kirklees CCG) wanted to better appreciate the potential and impact of how Better Care Fund monies were being utilised, and whether there were more effective ways to analyse or target the work. PI Care and Health were selected for this work based on their existing work in this field, their clarity in defining the detail of what could be done and how, their engagement and attitude, ability to deliver and price. 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. 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. 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.

Objectives:

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. 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 CCG 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.