NHS Digital Data Release Register - reformatted

NHS Solihull Ccg projects

57 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).


🚩 NHS Solihull Ccg was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Solihull Ccg may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

Project 1 — NIC-41134-T4K0J

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Y ()

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

Purposes: ()

Sensitive: Sensitive

When:2017.09 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Local Provider Data - Acute
  2. Local Provider Data - Demand for Service
  3. Local Provider Data - Demand For service
  4. Local Provider Data - Diagnostic Services
  5. Local Provider Data - Emergency Care
  6. Local Provider Data - Mental Health
  7. Local Provider Data - Other not elsewhere classified
  8. Local Provider Data - Population Data
  9. Maternity Services Dataset
  10. Local Provider Data - Community
  11. Improving Access to Psychological Therapies Data Set
  12. Mental Health Minimum Data Set
  13. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  14. SUS for Commissioners
  15. Public Health and Screening Services-Local Provider Flows
  16. Primary Care Services-Local Provider Flows
  17. Population Data-Local Provider Flows
  18. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  19. Mental Health-Local Provider Flows
  20. Mental Health Services Data Set
  21. Mental Health and Learning Disabilities Data Set
  22. Maternity Services Data Set
  23. Experience, Quality and Outcomes-Local Provider Flows
  24. Emergency Care-Local Provider Flows
  25. Diagnostic Services-Local Provider Flows
  26. Diagnostic Imaging Dataset
  27. Demand for Service-Local Provider Flows
  28. Community-Local Provider Flows
  29. Children and Young People Health
  30. Ambulance-Local Provider Flows
  31. Acute-Local Provider Flows
  32. SUS (Accident & Emergency, Inpatient and Outpatient data)
  33. Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Primary Care, Public Health & Screening services
  34. Children and Young People's Health Services Data Set
  35. Local Provider Data - Ambulance
  36. Local Provider Data - Primary Care
  37. SUS Accident & Emergency data
  38. SUS Admitted Patient Care data
  39. SUS Outpatient data

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number to undertake invoice validation on behalf of the CCG. In order to support commissioning of patient care by validating non-contracted activity in the CCG, this data is required for the purpose of invoice validation. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF.

Risk Stratification
This is an application to use SUS data identifiable at the level of NHS number 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.

Pseudonymised – SUS and Local Flows
Application for the CCG 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs linked and pseudonymised data to provide intelligence to support commissioning of health services. The linked, 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 the HSCIC will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

Invoice Validation
1) Financial validation of activity
2) CCG Budget control
3) Commissioning and performance management
4) Meeting commissioning objectives without compromising patient confidentiality
5) The avoidance of misapproproation of public funds to ensure the on-going 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 and pathways.
2) 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) flows
3) Commissioning cycle support for grouping and re-costing previous activity
4) Enables monitoring of:
a) CCG outcome indicators
b) Non-financial validation of patient level data
c) Successful delivery of integrated care within the CCG
d) Checking frequent or multiple attendances to improve early intervention and avoid admissions
e) Commissioning and performance management
5) Feedback to NHS service providers on data quality at an aggregate level

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways.
2) Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3) Health economic modelling using:
(a) Analysis on provider performance.
(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.

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 with no identifiers

3) Record level output will be available for commissioners in anonymised or pseudonymised format.

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 acute / community / mental health quality matrix.
6) Clinical coding reviews / audits.
7) Budget reporting down to individual GP Practice level.

Processing:

Central Midlands DSCRO will apply Type 2 objections (from 1st October 2016 onwards) before any identifiable data leaves the DSCRO.
Invoice Validation
1) Central and Midlands DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the Arden and GEM CSU (Data Processor 2).

2) The CSU carry out the following processing activities within the CEfF for invoice validation purposes:

a) Checking the individual is registered to a particular Clinical Commissioning Group (CCG) by using the derived commissioner field in SUS 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 system access and reports provided by the HSCIC to confirm the payments are:
- In line with Payment by Results tariffs
- are in relation to a patient registered with a CCG GP or resident within the CCG area.
- The health care provided should be paid by the CCG in line with CCG guidance. 
3) The CCG are notified of that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between Arden and GEM CSU and the provider meaning that no data needs to be sent to the CCG. The CCG only receives notification to pay.

Risk Stratification
1) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from Central and Midlands Data Services for Commissioners Regional Office (DSCRO) to the data processor.
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 Midlands and Lancashire CSU (Data Processor 1), who hold the SUS data within the secure Data Centre on N3.
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 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.
5) Midlands and Lancashire 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.
6) Once Midlands and Lancashire CSU has completed the processing, the CCG can dial in to the online system via N3 connection to access the data anonymised at patient level.

Pseudonymised – SUS and Local Flows
1) Central and Midlands Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. Central and Midlands DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2) Data quality management of data is completed by the DSCRO and the identifiable data is then passed securely to North England CSU for the addition of derived fields, linkage of data sets and analysis.
3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4) Patient level data will not be shared outside of the CCG. External aggregated reports only.

Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1) Central and Midlands Data Services for Commissioning Regional Office (DSCRO) will receive a flow of pseudonymised patient level data for each CCG for Mental Health (MHSDS, MHMDS, MHLDDS), Improving Access to Psychological Therapies (IAPT), Maternity (MSDS), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes
2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to Midlands and Lancashire CSU for the addition of derived fields, linkage of data sets and analysis. Linkage is not with other datasets just between the data contained within the dataset itself.
3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level.
6) Patient level data will not be shared outside of the CCG. External aggregated reports only with small numbers suppressed with HSCIC guidance.