NHS Digital Data Release Register - reformatted

NHS Rotherham Ccg

Project 1 — NIC-21918-G7F4P

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 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 in line with the HES analysis guide can be shared.

Objectives:

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


Project 2 — NIC-22495-V5H4T

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:

PROCESS 1: To provide risk profiling, calculated on activity data from secondary and primary care. As part of the risk stratification processing activity detailed above, the GP have access to the Optum HealthNumerics portal for reports which presents to them their registered patients and associated risk score. The GP can access the Optum HealthNumerics portal which is a secure portal at any time which will support MDT discussions around ongoing patient care. There are two views available, one is anonymised and the other identifiable. GP practices may give access to CCG staff and they determine the correct level of access, this is purely a GP managed initiative, Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd do not give permission to other users except for the GP. Optum have controls including a form of authorization for all CCG users. Practices would provide a list of their users and Optum would obtain new authorizations normally through the Practice Manager or Lead GP named on the Sharing Agreement. (CCGs users have an anonymised view of the data and are unable to ‘drill-down to patient specific information, so Optum would only provide this access for any users not authorised by a suitably qualified individual, Where there is any uncertainty, Optum as Data Processor would check with the Lead Contact at the CCG.) No record-level data will be shared with any other third party organisations. PROCESS 2: 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. The GP practice can access the RAIDR tool, which is a secure portal, at any time which will support MDT 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 data will be shared with any other third party organisations.

Processing:

PROCESS 1: The data processor agrees to process data only for the purposes of risk stratification only. Processing activities: Processing of SUS Data for the purposes of Risk Stratification includes landing, processing and scoring and publication. 1. Landing Prior to the release of SUS data by DSCRO Yorkshire, Type 2 objections will be applied and the relevant patients data redacted. DSCRO Yorkshire securely transfer the SUS data identifiable at the level of NHS number to Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd. Data is landed and processed in an access restricted data centre located at Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd hosted data warehouse. Data is refreshed maintaining 1 year of data visible only. Only named individuals have access to process the raw data. All users undertake regular IG training, in line with IGT & ISO 27001:2013 requirements. 2. Processing & Scoring Data is processed on a monthly basis. 2.1. Cleaning and quality checks are carried out and documented. 2.2. Creation of Risk Stratification dataset. 2.3. Risk Stratification dataset processed through Optum Risk Stratification Algorithm to produce a Risk Stratified scoring dataset. 3. Publication Outputs are available to GP practices (for their own patients only) via the Optum HealthNumerics portal. Access to the portal is via role-based access. All usage of its tools is audited which is controlled by Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd, practices can apply for this information. Record level data, identifiable at the level of NHS number, is only available to named individuals within the GP Practices who have a legitimate relationship with the patient determined by the practice. The web-portal is accessed by the GP using a username and password. The GP have direct access to any underlying patient level SUS data where they can see all aspects of the inpatient and outpatient, A&E and primary care activity. The GP also has access to the diagnosis data via both SUS data and the primary care data. PROCESS 2: The data processor agrees to process data only for the purposes of risk stratification. Processing activities: 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 also 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 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 (for their own patients only) who have a legitimate relationship with the patient. 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 organisation, except 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.

Objectives:

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


Project 3 — NIC-60433-X9Z5B

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 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.

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.


Project 4 — NIC-63161-C6S8V

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 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. It is expected that all of the aforementioned will lead to improved patient experience through more effective direct patient care services.

Outputs:

Data Processor 1 - Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd 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 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. The Optum contract will cease in 31st March 2017, all access will end at this date. All identifiable data held by Optum for the purpose of Risk Stratification will be destroyed no later than 1st April 2017. Data destruction certificates will be completed for all Identifiable data previously stored for the purpose of Risk Stratification. Data Processor 2 - eMBED Health Consortium To provide risk profiling, calculated on activity data from secondary and primary care. As part of the risk stratification processing activity detailed above, the GP have access to the eMBED Dr Foster tool for reports which presents to them their registered patients and associated risk score. The only identifier to be provided to the GP is the NHS number of their registered patient. The GP can access the eMBED Dr Foster tool which is a secure portal at any time which will support MDT discussions around ongoing patient care. The GP would be able to copy and paste the NHS number presented on screen to any other program and then save it, in order to maintain a risk register of their patients and perform the key aspects of this risk stratification role. CCG staff who have been granted access to the secure portal can only access aggregated output / reports. eMBED staff who have been granted access to the secure portal can only access aggregated suppressed data at GP practice level. The eMBED BI team have access to aggregated data with small number suppression. Where instructed by the CCG, eMBED will look at patterns of ‘admission risk’ across the CCG and the changes over time at practice and CCG level. The analysis and interpretation of the data by eMBED BI will help commissioners determine where additional support/services might be best deployed to mitigate “admission risk”, and to monitor the outcome of such service changes. This information will only be sent to the relevant CCG.

Processing:

Processor 1: Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd The data processor agrees to process data only for the purposes of risk stratification only. Processing of SUS Data for the purposes of Risk Stratification includes landing, processing and scoring and publication. 1. Landing Prior to the release of SUS data by Yorkshire DSCRO, Type 2 objections will be applied and the relevant patients data redacted. DSCRO Yorkshire securely transfer the SUS data identifiable at the level of NHS number to Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd. Data is landed and processed in an access restricted data centre located at Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd hosted data warehouse. Data is refreshed maintaining 1 years of data visible only. Only named individuals have access to process the raw data. All users undertake regular IG training, in line with IGT & ISO 27001:2013 requirements. 2. Processing & Scoring Data is processed on a monthly basis. 2.1. Cleaning and quality checks are carried out and documented. 2.2. Creation of Risk Stratification dataset. 2.3. Risk Stratification dataset processed through Optum Risk Stratification Algorithm to produce a Risk Stratified scoring dataset. 3. Publication Outputs are available to GP practices via the Optum Health Numerics portal. Access to the portal is via role-based access. All usage of its tools is audited which is controlled by Optum Healthcare Solutions (UK) Ltd incorporating UnitedHealth UK Ltd, practices can apply for this information. . Record level data, identifiable at the level of NHS number, is only available within the GP Practices who have a legitimate relationship with the patient only The web-portal is accessed by the GP using a username and password. The GP have direct access to any underlying patient level SUS data where they can see all aspects of the inpatient and outpatient, A&E and primary care activity. The GP also has access to the diagnosis data via both SUS data and the primary care data. Processor 2 : eMBED Health Consortium* (Kier Business Services Limited and Dr Foster Limited): Processing of SUS Data for the purposes of Risk Stratification includes landing, processing, staging and publication. DSCRO – part of NHS Digital - receive a flow of identifiable SUS data for the CCG from the SUS Repository. 1. Landing Prior to the release of SUS data by DSCRO, Type 2 objections will be applied and the relevant patient’s data redacted. DSCRO securely transfer the SUS data identifiable at the level of NHS number to eMBED. Data is landed and processed in an access restricted server located at Dr Foster’s Head Office (Dorset Rise, London). The SUS dataset for Risk Stratification purposes is recorded on the Dr Foster Ltd Data Asset Register (DAR) and allocated a unique Asset Tag and classification; in addition a Date of Destruction is recorded along with other contractual requirements relating to the publication of these data. Once the data has been secured within the database the original SUS PCD data file is securely destroyed using CESG approved shredding software which produces a certificate of destruction. The certificate is referenced on the Data Asset Register. Only named substantive employees have access to process the data. All users undertake regular IG training, in line with IGT & ISO 27001:2013 requirements. 2. Processing (ETL Extract, Transform & Load) Data is processed on a monthly basis, which follows Dr Foster’s audited ETL process. 2.1. Cleaning and quality checks are undertaken. 2.2. Creation of Risk Stratification dataset. 2.3. Risk Stratification dataset processed through Dr Foster’s Risk Stratification Algorithm to produce a Risk Stratified dataset 3. Staging Data is landed to a secure staging area for final quality checks using the Dr Foster Analysis Toolkit in an offline Q/A environment. A named QA analyst undertakes the quality checks. 4. Publication Outputs are available to eMBED, the CCG and the GP practices via the eMBED Dr Foster Toolkit. Access to the toolkit is via role-based access. All usage of its tools is audited. Record level data, identifiable at the level of NHS number, is only available to named individuals within the GP Practices for their own patients only who have a legitimate relationship with the CCG or where an individual working within a GP Practice has the authorisation of their Caldicott Guardian to access patient level information, including sensitive items, for the purposes of conducting Risk Stratification for case finding. (The GP user is prompted to re-enter their eMBED Dr Foster Tool password in order to view patient NHS Numbers.) An audit trail of the data accessed is reported on a monthly basis to GP practices and the GPs’ Caldicott Guardian.) The Risk stratification tool updates patients risk scores on a monthly basis and will be the source that General Practices and their Caldicott Guardian use to review their patients’ risk scores. The tool allows an authenticated user to generate an Excel report of risk for patients at their practice. The CCG has an aggregated with small number suppression view only of Risk Stratification for commissioning purposes based on their related GP practices. eMBED CSU can access the eMBED Dr Foster Tool but only have access to aggregated with small number suppression data at GP practice level. eMBED Business Intelligence (BI) staff will be active in providing added value, additional support and further analysis to CCG customers where required and therefore require an aggregated with small number suppressions data. No record-level SUS is provided to any other organisation.

Objectives:

To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a) (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


Project 5 — NIC-90710-D2P5L

Opt outs honoured: N, Y

Sensitive: Sensitive

When: 2017/03 — 2018/02.

Repeats: Ongoing

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

Categories: Anonymised - ICO code compliant, Identifiable, Identifiable

Datasets:

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

Benefits:

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

Outputs:

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

Processing:

Invoice Validation Data Processor 4 - NHS Rotherham Clinical Commissioning Group 1. SUS Data is obtained from the SUS Repository by Yorkshire Data Services for Commissioners Regional Office (DSCRO). 2. Yorkshire DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) located in the CCG. 3. The CEfF conduct the following processing activities for invoice validation purposes: a. Checking the individual is registered to the Clinical Commissioning Group (CCG) by using the derived commissioner field in SUS and associated with an invoice from the SUS data flow to validate the corresponding record in the backing data flow b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. In relation to a patient registered with the CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  4. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved Risk Stratification Data Processor 2 - eMBED Identifiable SUS data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO). 1. 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. 2. Identifiable GP Data is securely sent from the GP system to eMBED. 3. SUS data is linked to GP data in the risk stratification tool by the data processor. 4. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier 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. 5. 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. 6. 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. Data Processor 3 - Attain Health Management Services Ltd 1. Yorkshire Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Yorkshire 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, linkage of data sets and analysis. 3. North England CSU also receive Identifiable Social care data from providers This data is kept secure and separate from any other data and is pseudonymised once it has entered the CSU. Any identifiable data is then destroyed. 4. North of England CSU then link and process the pseudonymised data and pass the processed, pseudonymised and linked data to Attain. 5. Attain analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning and then send the pseudonymised data to the CCG 6. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG. 7. Data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared. Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDS 1. 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. Data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared.

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), the CCG receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (b)/2013. The data is required for the purpose of invoice validation. The NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. Risk Stratification To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care. Commissioning (Pseudonymised) – SUS and Local Flows To use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. 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.