DSfC - NEL Joint DC CCG App
NHS North East London ICB · Sub ICB Location
Listed under NHS North East London Integrated Care Board.
Expired The latest version ended on 16 October 2023. The September 2026 register still lists the agreement, but its term has passed.
- Reference
- DARS-NIC-129507-J0H0D
- Latest version
- v4.4
- Term of latest version
- 17 October 2020 to 16 October 2023
- Start date
- Before 14 December 2019
- Data controller
- Joint Data Controller
- Commercial purposes
- No
- Sublicensing
- No
- Files released to date
- 0
Why the data was released
Objective for processing
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCGs' area.
CCGs involved in this agreement:
NHS Waltham Forest CCG
NHS City and Hackney CCG
NHS Redbridge CCG
NHS Newham CCG
NHS Barking and Dagenham CCG
NHS Havering CCG
NHS Tower Hamlets CCG
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
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.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
The pseudonymised data is required to for the following purposes:
§ Population health management:
· Understanding the interdependency of care services
· Targeting care more effectively
· Using value as the redesign principle
§ Data Quality and Validation – allowing data quality checks on the submitted data
§ Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§ Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§ Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
§ Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
§ Support measuring the health, mortality or care needs of the total local population
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.
Processing for commissioning will be conducted by North East London Commissioning Support Unit and Queen Mary University of London.
Queen Mary University of London (QMUL) host a clinical effectiveness group. The group evaluates clinical outcomes and recommend best practice with regard to long term conditions and other health priorities within the area. This processing was previously approved as part of 3 separate agreements in what was described as 3 separate flows of data. The data analysed by QMUL was supplied as 'cuts' of the larger SUS+ extract under this agreement. The cuts are minimised to the receiving CCG's geographical coverage and only for 3 particular CCGs; NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG. Any access to other data is not permitted. This data is minimised by locations as described in this point, as well as by time period, the University may only use the latest available as well as the previous 3 years of data.
Processing activities
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.
Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
The processing of SUS+ data by Queen Mary University of London on behalf of NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG is limited to these 3 CCGs, however, liability of this Data Sharing Agreement still remains with all 7 CCGs under the joint data controller responsibilities set out within the Data Sharing Framework Contracts each CCG has approved.
ONWARD SHARING:
Patient level data will not be shared outside of the CCGs unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.
Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.
SEGREGATION:
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.
All access to data is auditable by NHS Digital.
DATA MINIMISATION
Data Minimisation in relation to the data sets listed within this agreement are listed below. This also includes the purpose on which they would be applied -
For the purpose of Commissioning:
• Patients who are normally registered and/or resident within the NHS Waltham Forest CCG, NHS City and Hackney CCG, NHS Redbridge CCG, NHS Newham CCG, NHS Barking and Dagenham CCG, NHS Havering CCG and NHS Tower Hamlets CCG (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where NHS Waltham Forest CCG, NHS City and Hackney CCG, NHS Redbridge CCG, NHS Newham CCG, NHS Barking and Dagenham CCG, NHS Havering CCG, and NHS Tower Hamlets CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of NHS Waltham Forest CCG, NHS City and Hackney CCG, NHS Redbridge CCG, NHS Newham CCG, NHS Barking and Dagenham CCG, NHS Havering CCG and NHS Tower Hamlets CCG - this is only for commissioning and relates to both national and local flows.
• QMUL may only access SUS+ data relating to those patients resident and/or registered within NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG. Any access to other data is not permitted.
Interxion & Ark do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
NHS North & East London Commissioning Support Unit use Cloud based processing and therefore will use Microsoft Azure Cloud as a processing location. Microsoft Limited provide Cloud Services for NHS North & East London Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
12. Civil Registries Data (CRD) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
Data quality management and pseudonymisation is completed within the DSCRO.
Datasets 1 – 14 are pseudonymised using one key.
The data sets are then disseminated as follows:
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS). Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT) Civil Registries Data (CRD), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI) data only is securely transferred from the DSCRO to NHS North & East London Commissioning Support Unit.
2. A) Dataset 1
i) NHS North East London Commissioning Support Unit add derived fields.
ii) The Clinical Effectiveness Group, hosted by Queen Mary University of London, access pseudonymised SUS+ on NHS North and East London Commissioning Support Unit servers. All access to data is managed under role-based access controls (RBAC). Users can only access data authorised by their role and the tasks that they are required to undertake.
iii) The Clinical Effectiveness Group, hosted by Queen Mary University of London, may only access data relating to those patients resident and/or registered within NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG. Any access to other data is not permitted. This data is minimised by locations as described in this point, as well as by time period the University may only use the latest available as well as the previous 3 years of data.
iv) NHS North East London Commissioning Support Unit will provide the mechanism to provide access via controlled views and maintain the access controls using RBAC via the NELIE support helpdesk. Approval will be granted by appointed approvers on behalf of NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG.
v) Queen Mary University of London process the data on behalf of NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG to evaluate clinical outcomes and recommend best practice with regard to long term conditions and other health priorities within the area.
vi) Aggregation of required data for CCG management use will be completed by Queen Mary University of London or the CCG as instructed by the CCG.
vii) Each CCG will only receive data relating to its own CCG. Therefore:
- NHS City and Hackney CCG will only receive data relating to the patients registered and/or resident with NHS City and Hackney CCG.
- NHS Newham CCG will only receive data relating to the patients registered and/or resident with NHS Newham CCG.
- NHS Tower Hamlets CCG will only receive data relating to the patients registered and/or resident with NHS Tower Hamlets CCG.
viii) Patient level data will not be shared outside of the CCGs and will only be shared within the CCGs on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement.
ix) External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
B) Datasets 1 – 14
i) NHS North East London Commissioning Support Unit add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
ii) Allowed linkage is between the data sets 1 - 14.
iii) NHS North East London Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCGs.
iv) Aggregation of required data for CCG management use will be completed by NHS North East London Commissioning Support Unit or the CCG as instructed by the CCGs.
v) 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 as set out within NHS Digital guidance applicable to each data set.
Expected output
Commissioning
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.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most frequent users (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts
Expected measurable benefits
Commissioning
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. Financial and 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.
7. 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.
8. 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.
9. 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.
10. 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.
11. Better understanding of the health of and the variations in health outcomes within the population to hel
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
19. Assists commissioners to make better decisions to support patients and drive changes in health care
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. Allow analysis of health care provision to 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.
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
23. Monitoring of entire population, as a pose to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
Benefits reported so far
Not stated in the register.
Datasets on the latest version
Legal basis for provision: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'
| Dataset | Type of data | Sensitivity | Frequency | Confidential data |
|---|---|---|---|---|
| Acute-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Ambulance-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Children and Young People Health | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Civil Registration - Births | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Civil Registrations of Death | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Community Services Data Set (CSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Community-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Demand for Service-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Diagnostic Imaging Data Set (DID) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Diagnostic Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| e-Referral Service for Commissioning | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Emergency Care-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Experience, Quality and Outcomes-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Improving Access to Psychological Therapies (IAPT) v1.5 | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Maternity Services Data Set | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health and Learning Disabilities Data Set (MHLDDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health Minimum Data Set (MHMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health Services Data Set (MHSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| National Diabetes Audit | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Patient Reported Outcome Measures (PROMs) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Personal Demographic Service | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Population Data-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Primary Care Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Public Health and Screening Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Summary Hospital-level Mortality Indicator (SHMI) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| SUS for Commissioners | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
Files released
Files released counts only files released externally by DARS. Access granted in NHS England's own systems, such as its Secure Data Environment, is not included.
No files recorded as released under this agreement.
Version history
The register lists each renewal of this agreement as a separate row. This site has 3 versions — earlier versions existed before this site's records begin.
DARS-NIC-129507-J0H0D-v4.4 17 October 2020 to 16 October 2023
- Title
- DSfC - NEL Joint DC CCG App
- Commercial
- No
- Sublicensing
- No
- Datasets
- 29
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Personal Demographic Service; Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; Summary Hospital-level Mortality Indicator (SHMI); SUS for Commissioners
What changed from DARS-NIC-129507-J0H0D-v3.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-10-17 | |
| End date | 2023-10-16 | |
| Acute-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Ambulance-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Children and Young People Health: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registration - Births: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registrations of Death: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community Services Data Set (CSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Demand for Service-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Imaging Data Set (DID): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Emergency Care-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Experience, Quality and Outcomes-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Improving Access to Psychological Therapies Data Set_v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Maternity Services Data Set v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Minimum Data Set (MHMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Services Data Set (MHSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health and Learning Disabilities Data Set (MHLDDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Diabetes Audit: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Patient Reported Outcome Measures (PROMs): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Population Data-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Primary Care Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Public Health and Screening Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| SUS for Commissioners: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' |
Datasets: + Personal Demographic Service; + Summary Hospital-level Mortality Indicator (SHMI); + e-Referral Service for Commissioning
Objective for processing
[10 paragraphs unchanged]
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
[1 paragraph unchanged]
The CCGs will work proactively and collaboratively with the other CCGs in the region to redesign services across boundaries to integrate services. Collaborative sharing is required for CCGs to understand these requirements.
[24 paragraphs unchanged]
- Civil Registries Data (CRD)
(Births and Deaths)
(Births)
- Civil Registries Data (CRD) (Deaths)
[2 paragraphs unchanged]
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
[1 paragraph unchanged]
§
Population health management:
•
·
Understanding the interdependency of care services
•
·
Targeting care more effectively
•
·
Using value as the redesign principle
§
Data Quality and Validation – allowing data quality checks on the submitted data
§
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§
Service redesign
§
Health Needs Assessment – identification of underlying disease prevalence within the local population
§
Patient stratification and predictive modelling - to
identify specific
highlight cohorts of
patients at risk of requiring hospital admission and other avoidable factors such
[7 words unchanged]
executed against linked de-identified data, and identification of future service delivery models
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 CCGs' area based on the full analysis of multiple pseudonymised datasets.
§ Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
§ Support measuring the health, mortality or care needs of the total local population
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.
[2 paragraphs unchanged]
Processing activities
[23 paragraphs unchanged]
Interxion
& Ark
do not access data held under this agreement as they only supply
[19 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
NHS North & East London Commissioning Support Unit use Cloud based processing and therefore will use Microsoft Azure Cloud as a processing location. Microsoft
UK
Limited
provide Cloud Services for NHS North & East London Commissioning Support Unit
[36 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[25 paragraphs unchanged]
12. Civil Registries Data (CRD)
(Births and Deaths)
(Births)
13. National diabetes Audit (NDA)
13. Civil Registries Data (CRD) (Deaths)
14. Patient Reported Outcome Measures (PROMs)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
[3 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[35 words unchanged]
Registries Data (CRD), National Diabetes Audit (NDA) and Patient Reported Outcome Measures
(PROMs)
(PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI) data
only is securely transferred from the DSCRO to NHS North & East London Commissioning Support Unit.
[26 paragraphs unchanged]
Expected output
[34 paragraphs unchanged]
13. Identifying and managing preventable and existing conditions
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
b. Risk stratification to identify populations suitable for case management
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
c. Risk profiling and predictive modelling
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
d. Risk stratification for planning services for population cohorts
17. Removal of patients from Risk Stratification reports.
e. Identification of disease incidence and diagnosis stratification
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
14. Reducing health inequalities
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
b. Socio-demographic analysis
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
15. Managing demand
22. Allow Commissioners to better protect or improve the public health of the total local patient population
a. Waiting times analysis
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
b. Service demand and supply modelling
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
c. Understanding cross-border and overseas visitor
25. Investigate mortality outcomes for trusts
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support NMoC
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner and geography
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Expected measurable benefits
[27 paragraphs unchanged]
11. Better understanding of the health of and the variations in health outcomes within the population to
help understand local population characteristics.
hel
[2 paragraphs unchanged]
14. Reviewing current service provision
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
a. Cost-benefit analysis and service impact assessments to underpin service transformation across health economy
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
b. Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.)
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
c. Impact analysis for different models or productivity measures, efficiency and experience
17. Support of benchmarking for evaluating progress in future years.
d. Service and pathway review
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
e. Service utilisation review
19. Assists commissioners to make better decisions to support patients and drive changes in health care
15. Ensuring compliance with evidence and guidance
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
a. Testing approaches with evidence and compliance with guidance.
21. Allow analysis of health care provision to 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.
16. Monitoring outcomes
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
a. Analysis of variation in outcomes across population group
23. Monitoring of entire population, as a pose to only those that engage with services
17. Understanding how services impact across the health economy
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
a. Service evaluation
25. Monitor the quality and safety of the delivery of healthcare services.
b. Programme reviews
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
c. Analysis of productivity, outcomes, experience, plan, targets and actuals
d. Assessing value for money and efficiency gains
e. Understanding impact of services on health inequalities
18. Understanding how services impact on the health of the population and patient cohorts
a. Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this
b. Propensity matching and scoring
c. Triple aim analysis
19. Understanding future drivers for change across health economy
a. Forecasting health and care needs for population and population cohorts across the region
b. Identifying changes in disease trends and prevalence
c. Efficiencies that can be gained from procuring services across wider footprints, from new innovations
d. Predictive modelling
20. Delivering services that meet changing needs of population
a. Analysis to support policy development
b. Ethical and equality impact assessments
c. Implementation of NMOC
d. What do next years contracts need to include?
e. Workforce planning
21. Maximising services and outcomes within financial envelopes across health economy
a. What-if analysis
b. Cost-benefit analysis
c. Health economics analysis
d. Scenario planning and modelling
e. Investment and disinvestment in services analysis
f. Opportunity analysis
22. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
23. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
24. Provision of indicators of health problems, and patterns of risk within the commissioning region.
25. Support of benchmarking for evaluating progress in future years.
DARS-NIC-129507-J0H0D-v3.3 3 January 2020 to 2 January 2023
- Title
- DSfC - NEL Joint DC CCG App
- Commercial
- No
- Sublicensing
- No
- Datasets
- 26
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; SUS for Commissioners
What changed from DARS-NIC-129507-J0H0D-v2.13
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-01-03 | |
| End date | 2023-01-02 |
Objective for processing
[53 paragraphs unchanged] Processing for commissioning will be conducted by North East London Commissioning Support Unit and Queen Mary University of London. [1 paragraph unchanged]
Processing activities
[24 paragraphs unchanged]
NHS North & East London Commissioning Support Unit use Cloud based processing and therefore will use Microsoft Azure Cloud as a processing location. Microsoft UK provide Cloud Services for NHS North & East London Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
[30 paragraphs unchanged]
The data sets are
the
then
disseminated as follows:
[27 paragraphs unchanged]
Expected output
[19 paragraphs unchanged]
8. GP Practice level dashboard
reports include high flyers.
reports.
[5 paragraphs unchanged]
o Most
expensive patients
frequent users
(top 15%)
[77 paragraphs unchanged]
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Expected measurable benefits
[68 paragraphs unchanged] 22. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed. 23. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice. 24. Provision of indicators of health problems, and patterns of risk within the commissioning region. 25. Support of benchmarking for evaluating progress in future years.
Objective for processing
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCGs' area.
CCGs involved in this agreement:
NHS Waltham Forest CCG
NHS City and Hackney CCG
NHS Redbridge CCG
NHS Newham CCG
NHS Barking and Dagenham CCG
NHS Havering CCG
NHS Tower Hamlets CCG
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.
The CCGs will work proactively and collaboratively with the other CCGs in the region to redesign services across boundaries to integrate services. Collaborative sharing is required for CCGs to understand these requirements.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
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 CCGs' area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North East London Commissioning Support Unit and Queen Mary University of London.
Queen Mary University of London (QMUL) host a clinical effectiveness group. The group evaluates clinical outcomes and recommend best practice with regard to long term conditions and other health priorities within the area. This processing was previously approved as part of 3 separate agreements in what was described as 3 separate flows of data. The data analysed by QMUL was supplied as 'cuts' of the larger SUS+ extract under this agreement. The cuts are minimised to the receiving CCG's geographical coverage and only for 3 particular CCGs; NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG. Any access to other data is not permitted. This data is minimised by locations as described in this point, as well as by time period, the University may only use the latest available as well as the previous 3 years of data.
Expected output
Commissioning
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.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most frequent users (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support NMoC
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner and geography
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
DARS-NIC-129507-J0H0D-v2.13 14 December 2019 to 13 December 2022
- Title
- DSfC - NEL Joint DC CCG App
- Commercial
- No
- Sublicensing
- No
- Datasets
- 26
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; SUS for Commissioners
Objective for processing
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCGs' area.
CCGs involved in this agreement:
NHS Waltham Forest CCG
NHS City and Hackney CCG
NHS Redbridge CCG
NHS Newham CCG
NHS Barking and Dagenham CCG
NHS Havering CCG
NHS Tower Hamlets CCG
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.
The CCGs will work proactively and collaboratively with the other CCGs in the region to redesign services across boundaries to integrate services. Collaborative sharing is required for CCGs to understand these requirements.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- 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)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
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 CCGs' area based on the full analysis of multiple pseudonymised datasets.
Queen Mary University of London (QMUL) host a clinical effectiveness group. The group evaluates clinical outcomes and recommend best practice with regard to long term conditions and other health priorities within the area. This processing was previously approved as part of 3 separate agreements in what was described as 3 separate flows of data. The data analysed by QMUL was supplied as 'cuts' of the larger SUS+ extract under this agreement. The cuts are minimised to the receiving CCG's geographical coverage and only for 3 particular CCGs; NHS City and Hackney CCG, NHS Newham CCG and NHS Tower Hamlets CCG. Any access to other data is not permitted. This data is minimised by locations as described in this point, as well as by time period, the University may only use the latest available as well as the previous 3 years of data.
Expected output
Commissioning
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. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support NMoC
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner and geography
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment
Register history
When this agreement appeared in, or was edited in, each monthly edition of the register. Built by comparing every edition this site holds, the earliest of which is July 2021.
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July 2021 —
already listed in the earliest edition this site holds, so it may be older. 3 versions: DARS-NIC-129507-J0H0D-v2.13, DARS-NIC-129507-J0H0D-v3.3, DARS-NIC-129507-J0H0D-v4.4
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October 2022
Succeeded Applicant organisation: NHS North East London CCG succeeded by NHS North East London ICB from 1 July 2022, according to NHS ODS. Not counted as a change.Succeeded Data controllers: NHS North East London CCG succeeded by NHS North East London ICB from 1 July 2022, according to NHS ODS. Not counted as a change.
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December 2022
Register-wide edit DARS-NIC-129507-J0H0D-v2.13, DARS-NIC-129507-J0H0D-v3.3 — Datasets: legal basis: “
s261(1) and” taken out. Made to 639 agreements in this edition, so it is reported once, on the changes page, and not counted as an amendment of this agreement.
Cite this page
NHS England (2026) Data Uses Register, September 2026 edition, agreement DARS-NIC-129507-J0H0D, “DSfC - NEL Joint DC CCG App”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-129507-j0h0d/ (accessed [date]).
This address stays the same, but the page is rebuilt with each monthly edition, so the citation names the edition it shows. Every edition's data is kept in the facts store.
Source: datausesregister_september2026.xlsx, September 2026 edition of the NHS England Data Uses Register. Search that workbook for DARS-NIC-129507-J0H0D to see the original rows.