NHS Digital Data Release Register - reformatted

NHS Islington Ccg

Project 1 — NIC-55763-T6C5M

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
  • 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:

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 Commissioning (Pseudonymised) – SUS, Local Flows, Mental Health, 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. 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:

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 Commissioning (Pseudonymised) - SUS, Local Flows, Mental Health, CYPHS, IAPT and DIDs 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers.

Processing:

The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those administrative staff with authorised user accounts used for identification and authentication. Invoice Validation 1. SUS Data is obtained from the SUS Repository to North East London Data Services for Commissioners Regional Office (DSCRO). 2. North East London DSCRO de-identifies the data and pushes a one-way data flow of SUS data anonymised in line with the ICO Code of Practice and using the local identifiers into the Controlled Environment for Finance (CEfF) in the North East London CSU. 3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  4. The CCG are notified that the invoice has been validated and can be paid. 5. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider using the local patient ID and local event ID. The local identifiers must only be used for the purpose of contract monitoring to ensure sound financial management, challenge of costs or data between commissioner and provider and the prevention and possible investigation of any fraudulent or potentially fraudulent acts. 6. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. 7. Identifiable data from providers for the purpose of invoice validation will only flow when SUS data is not available for a particular service, this cannot be used to identify the pseudonymised SUS data provided for invoice validation. 8. Pseudonymised data cannot be used for the purpose of reidentification Commissioning (Pseudonymised)– SUS, Local Flows, Mental Health, MSDS, IAPT, CYPHS and DIDs 1. North East London Data Services for Commissioners Regional Office (DSCRO) obtains the following for commissioning purposes: 2. a flow of SUS identifiable data for the CCG from the SUS Repository. 3. identifiable local provider data for the CCG directly from Providers. 4. a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Children and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDs). 5. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage of data sets and analysis. 6. North East London CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 7. Aggregation of required data for CCG management use will be completed by the CSU 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. Pseudonymised data cannot be used for the purpose of reidentification

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data anonymised in line with the ICO Code of Practice and using the local identifiers to undertake invoice validation on behalf of the CCG. The CCG are advised by the CSU whether payment for invoices can be made or not. Commissioning (Pseudonymised) – SUS, Local Flows, Mental Health, Maternity, IAPT, CYPHS and DIDS To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services : - SUS - Local Flows - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Diagnostic Imaging Data Set (DIDS) The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.


Project 2 — NIC-95815-C3W0W

Opt outs honoured: N

Sensitive: Sensitive

When: 2017/03 — 2018/02.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • 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
  • Local Provider Data - Public Health & Screening services
  • 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. 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 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. 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. 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. In the first instance, GPs have access to pseudonymised patient level data of their own patients however they also have the ability to access NHS number of their patients following explicit action that initiates a re-identification of the pseudonymised NHS number. Any further identification of the patients will be completed by the GP on their own systems. 2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. 3. Record level output will be available for commissioners pseudonymised at patient level 4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient. Pseudonymised – SUS and Local Flows 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers. Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDs 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCG Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports include high flyers.

Processing:

The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those administrative staff with authorised user accounts used for identification and authentication. Invoice Validation 1. SUS Data is obtained from the SUS Repository to North East London Data Services for Commissioners Regional Office (DSCRO). 2. North East London DSCRO de-identifies the data and pushes a one-way data flow of SUS data anonymised in line with the ICO Code of Practice and using the local identifiers into the Controlled Environment for Finance (CEfF) in the North East London CSU. 3. The CSU carry out the following processing activities within the CEfF for invoice validation purposes: a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are: i. In line with Payment by Results tariffs ii. are in relation to a patient registered with a CCG GP or resident within the CCG area. iii. The health care provided should be paid by the CCG in line with CCG guidance.  4. The CCG are notified that the invoice has been validated and can be paid. 5. Any discrepancies or non-validated invoices are investigated and resolved between the CSU CEfF team and the provider using the local patient ID and local event ID. The local identifiers must only be used for the purpose of contract monitoring to ensure sound financial management, challenge of costs or data between commissioner and provider and the prevention and possible investigation of any fraudulent or potentially fraudulent acts. 6. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Risk Stratification 1. Identifiable SUS data is obtained from the SUS Repository by North East London Data Services for Commissioners Regional Office (DSCRO). 2. Data quality management, standardisation and pseudonymisation of the data is completed by North East London DSCRO and the pseudonymised (data anonymised in accordance with the ICO Code of Practice) record level data is transferred securely to North East London CSU, who hold the SUS data within the secure Data Centre on N3. 3. GP Data identifiable at the level of NHS number is securely sent from the GP system to North East London CSU. 4. North East London CSU pseudonymises the GP data using the same pseudo ID as SUS, but without requiring the NHS Number to be stored within the CSU. The pseudonymisation process uses a lookup table containing a salted NHS Number hash and Pseudo Id only (it does not contain NHS Number). 5. The lookup table consists of hash values for all possible NHS Numbers and their pseudonyms. The NHS Number hash is calculated by adding a salt (a secret string of characters) to the NHS Number and applying a cryptographic hash function to get the final hash value. Each NHS Number has a unique hash value. The hash function is non-reversible, i.e. for given the hash value it is not possible to mathematically calculate the input value. 6. The lookup table will only be used to pseudonymise GP Data for the purpose of Risk Stratification 7. The pseudonymised GP and SUS data is loaded into the risk stratification tool where the data is linked. 8. 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 GPs access the pseudonymised NHS number of their own patients however, following an explicit action, they also have the ability to access the NHS Number of those patients for the purpose of direct care. The GP request for the re-identification of a pseudonymised NHS Number is passed to the North East London DSCRO which returns the NHS Number. Any further identification of the patients will be completed by the GP on their own systems, using the revealed NHS Numbers. 9. North East London 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. 10. Once North East London CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level. Commissioning (Pseudonymised) – SUS and Local Flows 1. North East London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. North East London DSCRO also obtains identifiable local provider data for the CCG directly from Providers. 2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets, local flows and the datasets listed in the following section. 3. North East London CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning. 4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG. 5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place. Commissioning (Pseudonymised) – Mental Health, MSDS, IAPT, CYPHS and DIDs 1. North East London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging Dataset (DIDs) for commissioning purposes. 2. Data quality management and pseudonymisation of data is completed by North East London DSCRO and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields, linkage of datasets and analysis. 3. North East London CSU then pass the processed, pseudonymised and linked data to the CCG. 4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning 5. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG 6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared where contractual arrangements are in place.

Objectives:

Invoice Validation As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data anonymised in line with the ICO Code of Practice and using the local identifiers to undertake invoice validation on behalf of the CCG. The CCG are advised by the CSU whether payment for invoices can be made or not. 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 primarily using Pseudonymised data. For the purposes of direct care, GPs have the ability to access SUS data identifiable at the level of NHS number under S.251 CAG 7-04(a)/2013 following explicit action that initiates a re-identification. Commissioning (Pseudonymised) – SUS, Local Flows, Mental Health, Maternity, IAPT, CYPHS and DIDs To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services : - SUS - Local Flows - 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 Dataset (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. 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. No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.