NHS Digital Data Release Register - reformatted

NHS Redbridge Ccg

Project 1 — NIC-41646-V9N9J

Opt outs honoured: Y, N

Sensitive: Sensitive

When: 2016/12 — 2018/05.

Repeats: Ongoing

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

Categories: Identifiable, Anonymised - ICO code compliant, Identifiable

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
  • 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
  • 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)
  • SUS for Commissioners
  • Public Health and Screening Services-Local Provider Flows
  • Primary Care Services-Local Provider Flows
  • Population Data-Local Provider Flows
  • Other Not Elsewhere Classified (NEC)-Local Provider Flows
  • Mental Health-Local Provider Flows
  • Maternity Services Data Set
  • Experience, Quality and Outcomes-Local Provider Flows
  • Emergency Care-Local Provider Flows
  • Diagnostic Services-Local Provider Flows
  • Diagnostic Imaging Dataset
  • Demand for Service-Local Provider Flows
  • Community-Local Provider Flows
  • Children and Young People Health
  • Ambulance-Local Provider Flows
  • Acute-Local Provider Flows

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, Local Flows, 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 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. 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 located at Redbridge CCG which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk. 3. Record level output will be available for commissioners pseudonymised at patient level. 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, Local Flows, 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. Relevant controls are in place to ensure that the identifiable data is stored separately, under strict access control provisions, from the pseudonymised form (which is anonymised in accordance with the ICO Anonymisation Code of Practice). There will be no efforts made by the CCG or its Data Processor to link these datasets.

Processing:

North East London DSCRO will apply Type 2 objections before any identifiable data leaves the DSCRO. Invoice Validation 1. SUS Data is obtained from the SUS Repository by DSCRO North East London. 2. DSCRO North East London 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 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 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 that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved Risk Stratification 1. Identifiable SUS data is obtained from the SUS Repository by Data Services for Commissioners Regional Office (DSCRO) North East London. 2. Data quality management and standardisation of data is completed by DSCRO North East London and the data identifiable at the level of NHS number is transferred securely to the CCG (via North East London CSU download area), who hold the SUS data within the secure Data Centre on N3. 3. Identifiable GP Data is securely sent from the GP system to Redbridge CCG. 4. SUS data is linked to GP data in the risk stratification tool by the data processor (Redbridge CCG, who host the Health Analytics Risk Stratification Tool). 5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems. 6. The CCG who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication. 7. Once the CCG has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level. Pseudonymised – SUS, Local Flows, Mental Health, MSDS, IAPT, CYPHS and DIDS 1a. Data Services for Commissioners Regional Office (DSCRO) North East London obtains a flow of SUS identifiable data for the CCG from the SUS Repository. DSCRO North East London also obtains identifiable local provider data for the CCG directly from Providers. 1b. Data Services for Commissioners Regional Office (DSCRO) North East London 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 (DIDS) for commissioning purposes from NHS Digital. 2. Data quality management and pseudonymisation of data is completed by DSCRO North East London and the pseudonymised data is then passed securely to North East London CSU for the addition of derived fields and analysis. 3. North East London CSU links the datasets and passes the processed, pseudonymised, 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 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) (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. 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 Provider Data - 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 the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.


Project 2 — NIC-81417-R1V4C

Opt outs honoured: N

Sensitive: Sensitive

When: 2017/03 — 2018/05.

Repeats: Ongoing

Legal basis: Health and Social Care Act 2012

Categories: Anonymised - ICO code compliant

Datasets:

  • SUS Accident & Emergency data
  • SUS Admitted Patient Care data
  • SUS Outpatient data
  • Local Provider Data - Demand for Service
  • Local Provider Data - Diagnostic Services
  • Local Provider Data - Emergency Care
  • Local Provider Data - Mental Health
  • Local Provider Data - Other not elsewhere classified
  • Local Provider Data - Population Data
  • Maternity Services Dataset
  • Local Provider Data - Community
  • SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  • SUS for Commissioners
  • Emergency Care-Local Provider Flows
  • Community-Local Provider Flows
  • Ambulance-Local Provider Flows

Benefits:

1) Improved planning by better understanding patient flows through the urgent care healthcare system, thus allowing NHS England 111 to design appropriate pathways to improve patient flow. 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) Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics. 5) Effective Evaluation of new 111 Systems, such as the Patient Relationship Manager, where it can be determined whether intended Dispositions are in fact observed and obeyed by the Patient Population. 6) Allowing Repeat Callers and Callers with Care Plans to directly speak to a Clinician instead of a Call Handler; establishing the level of benefit to the Callers. 7) Establishment of a Body of Evidence, from which recommendations can be based (on evidence) for further improvements to the System. 8) Establishment of a Framework of Evaluation, to aid the evaluation of Pilots, where these are thought to impact on the Urgent and Emergency Care System.

Outputs:

Output from the data linkage/Patient Flows will provide aggregate reporting of number and percentage of population found to exhibit behaviour of interest; such as frequent attenders. 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 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 and Clinicians in the 111 Service; based on the Population’s prevalence of Repeat Callers and Callers with Care Plans (YTD). From analysis/review: Estalishing the effectiveness of the NHS Pathways-derived Dispositions; and the extent to which this impact on a Population (YTD). From analysis/review: Establishing the cost and Service impacts of introducing the NHS 111 PRM System in a new region (YTD). From analysis/review: Establishing the extent to which Costs and benefits from introducing the NHS 111 PRM System differs across the boroughs of Greater London. What factors or variables in a population contribute to such differences (YTD). From analysis/review: Establishing what aspects of the NHS 111 PRM System have proven effective across a majority of populations; and what features of the System would require improvement (YTD). From analysis/review: Determining how the NHS 111 PR System can by improved, based on the impct on the caller population (YTD).

Processing:

Commissioning (Pseudonymised) – SUS and Local Flows 1. North East London (NEL) Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. NEL 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 linked. Allowed linkage is between SUS data sets and local flows. 3. The DSCRO then pass the linked pseudonymised data securely to North East London CSU for the addition of derived fields and analysis 4. Business Intelligence specialists at NEL CSU have developed a stochastic algorithm which infers linkages between events based on Patient and Clinical Complaint; through participation in previous National Programmes, such as the NHSE 111 Learning & Development Programme Phase 1 & 2. It is this algorithm which will be employed to produce anonymised relationships for downstream statistical analyses (which will be carried out by NWL CLAHRC). 5. North East London CSU then pass the processed, pseudonymised and linked data to NWL CLAHRC. NWL CLAHRC analyse and evaluate the data to see patient journeys for pathways or service design, re-design and de-commissioning. 6. Aggregation of required data for CCG management use will be completed by NWL CLAHRC and sent to Redbridge CCG. 7. Redbridge CCG will share aggregate reports with small number suppression to the CCGs within the Health London Partnership. 8. Patient level data will not be shared outside of the Data Processors. External aggregated reports only with small number suppression can be shared 9. Redbridge CCG are the sole data controller and accept responsibility for all of the CCGs within the Health London Partnership. The Health London Partnership comprises of the below CCGs. NHS Redbridge CCG NHS Bexley CCG NHS Brent CCG NHS Bromley CCG NHS Barking and Dagenham CCG NHS Barnet CCG NHS Camden CCG NHS City and Hackney CCG NHS Enfield CCG NHS Haringey CCG NHS Havering CCG NHS Islington CCG NHS Newham CCG NHS Tower Hamlets CCG NHS Croydon CCG NHS Ealing CCG NHS Greenwich CCG NHS Hammersmith and Fulham CCG NHS Harrow CCG NHS Hillingdon CCG NHS Hounslow CCG NHS Kensington and Chelsea - West London CCG NHS Kingston CCG NHS Lambeth CCG NHS Lewisham CCG NHS Merton CCG NHS Richmond CCG NHS Southwark CCG NHS Sutton CCG NHS Waltham Forest CCG NHS Wandsworth CCG NHS Westminster - Central London CCG

Objectives:

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. In order to accurately evaluate and improve the NHS 111 Patient Relationship Manager (PRM) System the CCG requires the ability to link NHS 111 PRM Call processing to eventual outcomes in the wider Urgent and Emergency Care System. The SUS data will allow for linkage to Emergency Department’s (ED) and Urgent Care Centre’s (UCC, including Short Stay Admissions, in the DSCRO. That is, it is important to relate the attendance, and the outcomes from this attendance, in the wider Urgent and Emergency Care System; with the 111 call which initiated the Patient Journey. The accuracy and relevance of the processes in 111 can only be evaluated if the CCG understands how the Patient had their complaint ultimately resolved. It could be that callers to 111, who are associated with a specific Symptom Group and who received a particular disposition for Primary- or Self-Care; nevertheless end up in ED. In that case, the CCG will evaluate the effectiveness of the associated 111 processes. When a caller rings NHS 111, the disposition from from that call is a recommendation from the 111 System as to what the caller should do next, to resolve their clinical complaint. Most often, the disposition is in the form of a recommendation to attend a Service in person. The disposition, when given by a Call Handler, is derived by the NHS Pathways algorithm. One way to evaluate the accuracy of this algorithm with respect to a caller population, is to link the dispositions to the final outcomes of callers. This is achieved by linking the records of the different data sets by NEL CSU, by using the data linkage algorithm described above. A high degree of correspondence between the type of final Service attended; and the type of service given in the disposition, would indicate that for these callers the NHS Pathways algorithm is highly accurate. The PRM have introduced facilities in the System where repeat callers; and callers with a Care Plan, get connected to a clinician instead of a Call Handler. By analysing whether the final outcomes differ significantly for callers who spoke to a Call Handler; as compared to callers who spoke to a clinician; we can evaluate the impact on repeat callers and caller with a Care Plan, by the introduction of the PRM System.