Unofficial. This site is an experimental reformatting of data published by NHS England. It is not endorsed by NHS England. Always check the official Data Uses Register before relying on anything here.

3 CCGs within Coventry and Warwickshire STP - Comm, including GP data

NHS Coventry and Warwickshire ICB · Sub ICB Location

Listed under NHS Coventry and Warwickshire Integrated Care Board.

Expired The latest version ended on 15 April 2023. The September 2026 register still lists the agreement, but its term has passed.

Reference
DARS-NIC-238282-X0B6H
Latest version
v2.4
Term of latest version
16 April 2020 to 15 April 2023
Start date
Before 1 June 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:

This Agreement permits the use of 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 Sustainability Transformation Partnership (STP) area, which includes the following:

- Coventry and Rugby CCG

- Coventry and Warwickshire NHS Partnership Trust

- Coventry City Council

- George Eliot Hospital NHS Trust

- South Warwickshire CCG

- South Warwickshire NHS Foundation Trust

- University Hospitals Coventry and Warwickshire NHS Trust

- Warwickshire County Council

- Warwickshire North CCG

Only the CCGs will have access to patient level data, the other organisations will only have access to aggregated data in line with NHS Digital small suppression rules.

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 Sets (CRD) (Births and Deaths)

• Patient Reported Outcome Measures Data Set (PROMs)

• National Diabetes Audit Data Set (NDA)

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 CCGs wish to include pseudonymised primary care data in the population health management and patient stratification analyses to enable more comprehensive and patient/pathway focused analyses.

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.

Patient data historically sits in silos within various NHS services. Linking datasets including GP data enables commissioners to better understand the effective delivery of health and social care services for the populations they manage and not just for those directly receiving treatment. It supports commissioners to allocate resources as well as providing greater insight into the provision of services and into the health of the population.

Linking primary care and secondary care data supports with understanding a patient’s full journey across their pathway and across the community which can provide opportunities for understanding health needs pre and post treatment across numerous health services, for example, analysis has shown that those able to manage their health conditions (GP data) are less likely to attend Accident and Emergency and less likely to be admitted in an emergency (secondary care data). It can also support with coordinating discharge planning and integration of services as those receiving social care can be a key driver of demand for health and care.

Processing for commissioning, including the pseudo at source processing necessary for patient stratification and population health management will be conducted by NHS Arden and GEM Commissioning Support Unit.

The 3 CCGs of the STP programme have planned a number of initiatives and work-streams for local service providers to work together and develop new service models for the future delivery of high quality, efficient and effective services across Coventry and Warwickshire, for example the Out-of-Hospital Programme.

The STP and the CCGs now wish to engage the services of additional data processors to better utilise the potential provided through the linking of primary care data and secondary care data (previously approved) particularly for additional support with their population health management and patient stratification programme.

• South Warwickshire GP Federation Ltd (SWGP),

and

• South Warwickshire Foundation NHS Trust (SWFT)

These data processors will each bring their own specific expertise in analysing the pseudonymised datasets SWGP will apply their primary care expertise from experience, knowledge and insight about GP data and SWFT will apply their secondary care expertise from their associated experience, knowledge and insight regarding the hospital and community data. There will be a small team of analysts providing this support within each organisation, so access to data will be restricted, especially with the Provider Trust (SWFT).

The pseudonymised outputs of the analysis will be used by the CCGs to support their whole commissioning agenda, for example to support the CCGs with work around data quality and service re-design in both primary and secondary care. Pseudonymised outputs will also be used to feed into the interdisciplinary teams of clinical staff that will work across Coventry and Warwickshire. Only the GP Practice where the patient is registered will be able to re-identify patients and only when they need to do so for direct care purposes. GP Practices will make referrals to services as required.

Processing activities

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.

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 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 - i.e. employees, agents and contractors of the Data Recipient who may have access to that data)

Onward Sharing:

Patient level data will not be shared outside of the CCG other than specified within this agreement 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. In particular , the pseudonymised commissioning data which SWGP and SWFT will access as data processors to the CCGs will be held separately from any other data that they hold; controls around access to the data will ensure they will not be able to re-identify any data and they will not link to any data other than as listed in the NHS Digital DSA. The data will only be accessed by a small number of analysts.

All access to data is auditable by NHS Digital.

Data Minimisation:

Data Minimisation in relation to the data sets listed within the application 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 NHS Coventry and Rugby CCG, NHS South Warwickshire CCG and NHS Warwickshire North CCG (including historical activity where the patient was previously registered or resident in another commissioner).

and/or

• Patients treated by a provider where NHS Coventry and Rugby CCG, NHS South Warwickshire CCG and NHS Warwickshire North 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 Coventry and Rugby CCG, NHS South Warwickshire CCG and NHS Warwickshire North CCG - this is only for commissioning and relates to both national and local flows.

In addition to the dissemination of Cancer Waiting Times Data via the Data Services for Commissioners Reginal Office (DSCRO), the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement.

A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting

Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation).

Microsoft Supply Cloud Services to South Warwickshire GP Limited 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.

Coventry and Warwickshire Partnership NHS Trust supply IT infrastructure for the CCGs 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.

NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by NHS Oldham CCG) supply IT infrastructure for Arden and GEM Commissioning Support Unit and are therefore listed as data processors. 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.

Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust 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.

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 and Deaths)

13. Patient Reported Outcome Measures Data Set (PROMs)

14. National Diabetes Audit Data Set (NDA)

Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:

Data Processor 1 – NHS Arden and GEM Commissioning Support Unit

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) (Births and Deaths), Patient Reported Outcome Measures (PROMs) and National Diabetes Audit (NDA) only is securely transferred from the DSCRO to Arden and GEM Commissioning Support Unit..

2. NHS Arden and Greater East Midlands Commissioning Support Unit receive GP data (as points i-x)

3. Data listed within point 1 is then linked to the pseudonymised GP data and analysis is provided 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

4. NHS Arden and Greater East Midlands Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCGs.

5. Aggregation of required data for CCG management use will be completed by NHS Arden and Greater East Midlands Commissioning Support Unit or the CCG as instructed by the CCG.

6. Patient level data will not be shared outside of the CCGs, other than with their member GP Practices for each Practices own patients only and will only be shared within the CCGs 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 outside of this as set out within NHS Digital guidance applicable to each data set.

7. GP Practices may only re-identify data when they need to do so for direct care purposes.

GP data

i. Identifiable GP data is submitted to NHS Arden and Greater East Midlands Commissioning Support Unit.

ii. The data lands in a ring-fenced area for GP data only.

iii. A specific named individual within NHS Arden and Greater East Midlands Commissioning Support Unit acts on behalf of the GP practice. This person has access to a closed black box system (which includes a pseudonymisation process).

iv. The individual requests a pseudonymisation key from the DSCRO to use with the black box system. There will be a separate key specific to the pseudonymisation request and the key will only be used for that specific project. The key is specific to the pseudonymisation request. The access controls around the individual’s role does not give them access to the data once it has been passed on to the NHS Arden and Greater East Midlands Commissioning Support Unit.

v. The GP data is then pseudonymised using the black box and DSCRO issued key. The identifiable GP data is then deleted from the ring-fenced area.

vi. The data is then transferred into a separate part of NHS Arden and Greater East Midlands Commissioning Support Unit.

vii. NHS Arden and Greater East Midlands Commissioning Support Unit make a request to NHS Digital (DSCRO).

viii. The DSCRO send a mapping table to NHS Arden and Greater East Midlands Commissioning Support Unit.

ix. NHS Arden and Greater East Midlands Commissioning Support Unit overwrite the organisations specific pseudonymisation keys with the DSCRO provided keys.

x. The mapping table is then deleted.

Data Processor 2 – South Warwickshire GP Ltd

1. South Warwickshire GP Ltd will receive the linked pseudonymised primary care and secondary care data from Step 4, under Data Processor 1 processing activities from either NHS Arden and GEM CSU or from the CCG.

2. South Warwickshire GP Ltd will analyse the data with a focus on primary care and provide reports to the CCG and to the GP Practices as instructed by the CCG. South Warwickshire GP Ltd provide analytics to support population health management to help those providing patient care. The reports provide insight into a patient’s care and can highlight that a patient’s care needs to be reassessed to see if further intervention is required

3. Patient level data will not be shared outside of the CCGs, other than with their member GP Practices for each Practices own patients only and will only be shared within the CCGs 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 outside of this as set out within NHS Digital guidance applicable to each data set.

4. GP Practices may only re-identify data when they need to do so for direct care purposes.

5. South Warwickshire GP Ltd will not link this data to any other data that they hold or have access to.

Data Processor 3 – South Warwickshire NHS Foundation Trust

1. South Warwickshire NHS Foundation Trust will receive the linked pseudonymised primary care and secondary care data from Step 4, under Data Processor 1 processing activities from either NHS Arden and GEM CSU or from the CCG.

2. South Warwickshire NHS Foundation Trust will analyse the data to give greater insight into population health and patient stratification and provide reports to the CCG and to the GP Practices as instructed by the CCG. The reports will provide insight that will raise suggestions about the direct care of the patient.

3. Patient level data will not be shared outside of the CCGs, other than with their member GP Practices for each Practices own patients only and will only be shared within the CCGs 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 outside of this as set out within NHS Digital guidance applicable to each data set.

4. GP Practices may only re-identify data when they need to do so for direct care purposes.

5. South Warwickshire NHS Foundation Trust will not link this data to any other data that they hold or have access to.

Re-identification process for direct care

1. GP requires patient to be re-identified for the purpose of direct care

2. A re-id request is then automated through the CSU’s Business Intelligence (BI) Tool

3. The CSU assesses as to whether the request passes the specified Re-identification Process checks

4. If successful, the request is sent to the DSCRO for approval from the IAO/ IRO

5. DSCRO re-identifies the data item

6. National Data opt outs are not applied for the purpose of direct care

7. DSCRO send the identifiable data to the GP

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 High cost activity uses (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 patients 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.

South Warwickshire GP Ltd:

Using their knowledge of primary care data, South Warwickshire GP Ltd will be able to provide further analysis of the data, specifically around patient stratification. This will allow more detailed analysis of patients who may be at risk and provide prevention strategies. These reports will be made available to GP Practises for their own patients where they may only re-identify for direct care purposes

South Warwickshire GP Federation Ltd will be able to support practices by identifying these patients (through the pseudonymised route) for practices to re-identify as necessary for direct care and target suitable interventions and care plans and reducing the burden and workload on GP practices. The Federation will in turn have greater familiarity with the tool and its findings and share this knowledge and expertise with their practice population. They will be supporting the Practices with additional knowledge and expertise on getting the most out of data, tools and reporting but also supporting the CCG with expertise and knowledge of primary care data and GP systems and services.

South Warwickshire NHS Foundation Trust:

Using their knowledge of secondary care data, South Warwickshire NHS Foundation Trust give greater insight into population health and patient stratification and provide reports to GP Practises for their own patients where they may only re-identify for direct care purposes.

While the system is usually aware of the top 5% most complex patients, it is the next 15% of the population that the stratification analysis can identify which will provide vital information to multi-disciplinary teams that support GP Practices and the health system as a whole. The teams can then review these patients as directed by the GP Practices which they support to inform future care plans and interventions such as lifestyle management to assist in preventing hospitalisation. SWFT, as data processor on behalf of the CCGs, can fully support this process and work with the GP Practices to prioritise this patient cohort.

Following the COVID-19 pandemic, it will be more important than ever for the CCGs, Practices, SWFT and GP Federation to work collaboratively across the system to use Patient Stratification and Population Health Management techniques to better understand what that population needs during and post COVID-19. The analytical outputs will support in under-pinning the restoration of services and pathways and to help prioritise the needs of the population.

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 help understand local population characteristics.

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.

The CCGs want to utilise these 2 additional data processors because of their expertise in primary and secondary care data and the added resource they will provide. Therefore, the level of benefit overall will be much higher.

South Warwickshire GP Ltd

1. Higher level of patient stratification allowing direct care intervention

2. Knowledge sharing and best practices procedures for GP practises

3. Higher utilisation of the data and its tools allowing GP practices to easily identify areas of concern

South Warwickshire NHS Foundation Trust:

1. Greater insight into population and patient stratification using secondary care data

2. Higher level of patient stratification allowing direct care intervention

3. Allow further identification of possible factors relating to patients soon to be at risk, not previously identified

Benefits reported so far

The previous approval which permitted South Warwickshire CCG to analyse secondary care data linked to primary care (GP) data, provided significant benefit because the dataset was richer and enabled South Warwickshire CCG to analyse the full patient pathway across secondary care and primary care. For example, when they wanted to analyse the impact of projects that they have trialled where additional resources had been commissioned for specific cohorts of patients versus the pathway of patients who did not benefit from additional resources; they were able to more accurately evidence the benefit to the patients because of the richer dataset and were able then to justify funding wider roll-out of new services; or in some cases they were able to establish that the additional funding was not having the desired impact and enabled them to adjust the commissioned services.

However, the CCG’s ability to utilise the previous approval was limited because of their own lack of resource. The STP CCGs recognise that they can make even greater use of the combined secondary and primary care datasets by utilizing the resource and skills of the two new data processors (South Warwickshire NHS Foundation Trust and South Warwickshire GP Federation Ltd (SWGP). In addition the larger STP footprint will enable better pathway analysis as it allows more benchmarking and comparisons to be made across the region to better understand the population’s needs.

This is particularly pertinent following the coronavirus pandemic where prioritisation for restoration of services will be required as soon as possible and access to the data by both SWFT and the GP Federation to support the CCGs will aid restoration across the system and expedite this process. This will enable identification of the most at risk patients and target contact and intervention across the whole pathway – from out of hospital community, and primary care and acute secondary care.

Datasets on the latest version

Legal basis for provision: Health and Social Care Act 2012 – s261(2)(b)(ii)

Datasets approved under DARS-NIC-238282-X0B6H-v2.4
DatasetType of dataSensitivity FrequencyConfidential 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
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
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
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 2 versions — earlier versions existed before this site's records begin.

DARS-NIC-238282-X0B6H-v2.4 16 April 2020 to 15 April 2023
Title
3 CCGs within Coventry and Warwickshire STP - Comm, including GP data
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-238282-X0B6H-v1.5

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Fields changed from DARS-NIC-238282-X0B6H-v1.5
FieldWasBecame
Start date2019-06-012020-04-16
End date2022-05-312023-04-15

Objective for processing

Commissioning Commissioning: To This Agreement permits the use of pseudonymised data to provide intelligence to support the commissioning of health services. [23 words unchanged] the population within the Sustainability Transformation Partnership (STP) area, which includes the following CCGs: following: - NHS Coventry and Rugby CCG - Coventry and Warwickshire NHS South Warwickshire CCG Partnership Trust - NHS Warwickshire North CCG - Coventry City Council - George Eliot Hospital NHS Trust - South Warwickshire CCG - South Warwickshire NHS Foundation Trust - University Hospitals Coventry and Warwickshire NHS Trust - Warwickshire County Council - Warwickshire North CCG Only the CCGs will have access to patient level data, the other organisations will only have access to aggregated data in line with NHS Digital small suppression rules. [29 paragraphs unchanged] • Population health management: [3 paragraphs unchanged] • 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 [16 words unchanged] executed against linked de-identified data, and identification of future service delivery models. The CCGs wish to include pseudonymised primary care data in the population health management and patient stratification analyses to enable more comprehensive and patient/pathway focussed focused analyses. [1 paragraph unchanged] Patient data historically sits in silos within various NHS services. Linking datasets including GP data enables commissioners to fully better understand the effective delivery of health and social care services for the [17 words unchanged] as well as providing greater insight into the provision of services and to into the health of the population. Linking primary, primary care and secondary care data supports with understanding a patient’s full patient’s journey across their pathway and across the community which can provide opportunities for understanding health needs pre and post treatment across numerous health services. services, for example, analysis has shown that those able to manage their health conditions (GP data) are less likely to attend Accident and Emergency and less likely to be admitted in an emergency (secondary care data). It can also support with coordinating discharge planning and integration of services as those receiving social care can be a key driver of demand for health and care. For example, analysis has shown that those able to manage their health conditions (GP data) are less likely to attend A&E and less likely to be admitted in an emergency (secondary care data). It can also support with coordinating discharge planning and integration of services as those receiving social care can be a key driver of demand for health and care. Processing for commissioning, including the pseudo at source processing necessary for patient stratification and population health management will be conducted by NHS Arden and GEM Commissioning Support Unit. Processing for commissioning, including the pseudo at source processing for patient stratification and population health management will be conducted by NHS Arden and GEM Commissioning Support Unit. The 3 CCGs of the STP programme have planned a number of initiatives and work-streams for local service providers to work together and develop new service models for the future delivery of high quality, efficient and effective services across Coventry and Warwickshire, for example the Out-of-Hospital Programme. NHS Arden and GEM Commissioning Support Unit are the primary data processor for the three CCGs. NHS Arden and GEM Commissioning Support Unit use IT support services provided by NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by NHS Oldham CCG) and therefore both organisations are listed within the agreement as data processors although they only support the IT systems and do not access data. The STP and the CCGs now wish to engage the services of additional data processors to better utilise the potential provided through the linking of primary care data and secondary care data (previously approved) particularly for additional support with their population health management and patient stratification programme. The three CCGs are data controllers, but are listed as data processors in addition as processing occurs on the data the CCGs receive. The three CCGs use IT support services provided by Coventry and Warwickshire NHS Partnership Trust and therefore are listed within the agreement as data processor although they only support the IT systems and do not access data. • South Warwickshire GP Federation Ltd (SWGP), and • South Warwickshire Foundation NHS Trust (SWFT) These data processors will each bring their own specific expertise in analysing the pseudonymised datasets SWGP will apply their primary care expertise from experience, knowledge and insight about GP data and SWFT will apply their secondary care expertise from their associated experience, knowledge and insight regarding the hospital and community data. There will be a small team of analysts providing this support within each organisation, so access to data will be restricted, especially with the Provider Trust (SWFT). The pseudonymised outputs of the analysis will be used by the CCGs to support their whole commissioning agenda, for example to support the CCGs with work around data quality and service re-design in both primary and secondary care. Pseudonymised outputs will also be used to feed into the interdisciplinary teams of clinical staff that will work across Coventry and Warwickshire. Only the GP Practice where the patient is registered will be able to re-identify patients and only when they need to do so for direct care purposes. GP Practices will make referrals to services as required.

Processing activities

[4 paragraphs unchanged] Patient level data will not be linked other than as specifically detailed [15 words unchanged] and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data. Agreement. NHS Digital reminds all organisations party to this agreement of the need [17 words unchanged] that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: - i.e. employees, agents and contractors of the Data Recipient who may have access to that data) Onward Sharing Sharing: Patient level data will not be shared outside of the CCG other than specified within this agreement unless it is for the purpose of Direct Care, where it may [11 words unchanged] relationship with the patient and a legitimate reason to access the data. [1 paragraph unchanged] Segregation 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. 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. In particular , the pseudonymised commissioning data which SWGP and SWFT will access as data processors to the CCGs will be held separately from any other data that they hold; controls around access to the data will ensure they will not be able to re-identify any data and they will not link to any data other than as listed in the NHS Digital DSA. The data will only be accessed by a small number of analysts. [1 paragraph unchanged] Data Minimisation Minimisation: [7 paragraphs unchanged] In addition to the dissemination of Cancer Waiting Times Data via the Data Services for Commissioners Reginal Office (DSCRO), the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement. A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation). Microsoft Supply Cloud Services to South Warwickshire GP Limited 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. [2 paragraphs unchanged] Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust 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. Commissioning Commissioning: [41 paragraphs unchanged] 6. Patient level data will not be shared outside of the CCGs, [36 words unchanged] Agreement. External aggregated reports only with small number suppression can be shared outside of this as set out within NHS Digital guidance applicable to each data set. [4 paragraphs unchanged] iii. A specific named individual within NHS Arden and Greater East Midlands [7 words unchanged] the GP practice. This person has access to a closed black box type system (which includes a pseudonymisation process). [2 paragraphs unchanged] vi. The data moves is then transferred into a separate part of NHS Arden and Greater East Midlands Commissioning Support Unit. [4 paragraphs unchanged] Data Processor 2 – South Warwickshire GP Ltd 1. South Warwickshire GP Ltd will receive the linked pseudonymised primary care and secondary care data from Step 4, under Data Processor 1 processing activities from either NHS Arden and GEM CSU or from the CCG. 2. South Warwickshire GP Ltd will analyse the data with a focus on primary care and provide reports to the CCG and to the GP Practices as instructed by the CCG. South Warwickshire GP Ltd provide analytics to support population health management to help those providing patient care. The reports provide insight into a patient’s care and can highlight that a patient’s care needs to be reassessed to see if further intervention is required 3. Patient level data will not be shared outside of the CCGs, other than with their member GP Practices for each Practices own patients only and will only be shared within the CCGs 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 outside of this as set out within NHS Digital guidance applicable to each data set. 4. GP Practices may only re-identify data when they need to do so for direct care purposes. 5. South Warwickshire GP Ltd will not link this data to any other data that they hold or have access to. Data Processor 3 – South Warwickshire NHS Foundation Trust 1. South Warwickshire NHS Foundation Trust will receive the linked pseudonymised primary care and secondary care data from Step 4, under Data Processor 1 processing activities from either NHS Arden and GEM CSU or from the CCG. 2. South Warwickshire NHS Foundation Trust will analyse the data to give greater insight into population health and patient stratification and provide reports to the CCG and to the GP Practices as instructed by the CCG. The reports will provide insight that will raise suggestions about the direct care of the patient. 3. Patient level data will not be shared outside of the CCGs, other than with their member GP Practices for each Practices own patients only and will only be shared within the CCGs 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 outside of this as set out within NHS Digital guidance applicable to each data set. 4. GP Practices may only re-identify data when they need to do so for direct care purposes. 5. South Warwickshire NHS Foundation Trust will not link this data to any other data that they hold or have access to. Re-identification process for direct care 1. GP requires patient to be re-identified for the purpose of direct care 2. A re-id request is then automated through the CSU’s Business Intelligence (BI) Tool 3. The CSU assesses as to whether the request passes the specified Re-identification Process checks 4. If successful, the request is sent to the DSCRO for approval from the IAO/ IRO 5. DSCRO re-identifies the data item 6. National Data opt outs are not applied for the purpose of direct care 7. DSCRO send the identifiable data to the GP

Expected output

Commissioning Commissioning: [18 paragraphs unchanged] 8. GP Practice level dashboard reports include high flyers. reports. [4 paragraphs unchanged] a. o Patients at highest risk of admission b. Most expensive patients (top 15%) o High cost activity uses (top 15%) c. o Frail and elderly d. o Patients that are currently in hospital e. o Patients with most referrals to secondary care f. o Patients with most emergency activity g. o Patients with most expensive prescriptions h. o Patients recently moving from one care setting to another [2 paragraphs unchanged] 13. Profiling population health and wider determinants to identify and target those most in need 13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services. a. Understanding population profile and demographics 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. Identify patient cohorts with specific needs or who may benefit from interventions 15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support. c. Identifying disease prevalence. health and care needs for population cohorts 16. Understanding where patients 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. Contributing to Joint Strategic Needs Assessment (JSNA) 17. Removal of patients from Risk Stratification reports. e. Geographical mapping and analysis 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. Identifying and managing preventable and existing conditions South Warwickshire GP Ltd: a. Identifying types of individuals and population cohorts at risk of non-elective re-admission Using their knowledge of primary care data, South Warwickshire GP Ltd will be able to provide further analysis of the data, specifically around patient stratification. This will allow more detailed analysis of patients who may be at risk and provide prevention strategies. These reports will be made available to GP Practises for their own patients where they may only re-identify for direct care purposes b. Patient stratification to identify populations suitable for case management South Warwickshire GP Federation Ltd will be able to support practices by identifying these patients (through the pseudonymised route) for practices to re-identify as necessary for direct care and target suitable interventions and care plans and reducing the burden and workload on GP practices. The Federation will in turn have greater familiarity with the tool and its findings and share this knowledge and expertise with their practice population. They will be supporting the Practices with additional knowledge and expertise on getting the most out of data, tools and reporting but also supporting the CCG with expertise and knowledge of primary care data and GP systems and services. c. Risk profiling and predictive modelling South Warwickshire NHS Foundation Trust: d. Patient stratification for planning services for population cohorts Using their knowledge of secondary care data, South Warwickshire NHS Foundation Trust give greater insight into population health and patient stratification and provide reports to GP Practises for their own patients where they may only re-identify for direct care purposes. e. Identification of disease incidence and diagnosis stratification While the system is usually aware of the top 5% most complex patients, it is the next 15% of the population that the stratification analysis can identify which will provide vital information to multi-disciplinary teams that support GP Practices and the health system as a whole. The teams can then review these patients as directed by the GP Practices which they support to inform future care plans and interventions such as lifestyle management to assist in preventing hospitalisation. SWFT, as data processor on behalf of the CCGs, can fully support this process and work with the GP Practices to prioritise this patient cohort. 15. Reducing health inequalities Following the COVID-19 pandemic, it will be more important than ever for the CCGs, Practices, SWFT and GP Federation to work collaboratively across the system to use Patient Stratification and Population Health Management techniques to better understand what that population needs during and post COVID-19. The analytical outputs will support in under-pinning the restoration of services and pathways and to help prioritise the needs of the population. 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 16. 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 17. Care co-ordination and planning a. Planning packages of care b. Service planning c. Planning care co-ordination 18. 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 services to react to terror situations 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 New Models of Care (NMOC), Accountable Care Organisations (ACO), Sustainable Transformation Partnerships (STP) i. Identifying duplications in care j. Identifying gaps in care, missed diagnoses and triple fail events k. Analysing individual and aggregated timelines 19. 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 20. 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 21. 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 22. Comparing expected levels a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations 23. Comparing local targets & plan a. Monitoring of local variation in productivity, cost, outcomes, quality and experience b. Local performance dashboards by service provider, commissioner, geography, NMOC, STPs 24. Monitoring activity and cost compliance against contract and agreed plans a. Contract monitoring b. Contract reconciliation and challenge c. Invoice validation 25. 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 26. Improving provider data quality a. Coding audit b. Data quality validation and review c. Checking validity of patient identity and commissioner assignment 27. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services. 28. 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. 29. Clinical - understand reasons why patients are dying, what additional support services can be put in to support. 30. Understanding where patients 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. 31. Removal of patients from Risk Stratification reports. 32. 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

[30 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 The CCGs want to utilise these 2 additional data processors because of their expertise in primary and secondary care data and the added resource they will provide. Therefore, the level of benefit overall will be much higher. e. Service utilisation review South Warwickshire GP Ltd 15. Ensuring compliance with evidence and guidance 1. Higher level of patient stratification allowing direct care intervention a. Testing approaches with evidence and compliance with guidance. 2. Knowledge sharing and best practices procedures for GP practises 16. Monitoring outcomes 3. Higher utilisation of the data and its tools allowing GP practices to easily identify areas of concern a. Analysis of variation in outcomes across population group South Warwickshire NHS Foundation Trust: 17. Understanding how services impact across the health economy 1. Greater insight into population and patient stratification using secondary care data a. Service evaluation 2. Higher level of patient stratification allowing direct care intervention b. Programme reviews 3. Allow further identification of possible factors relating to patients soon to be at risk, not previously identified 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 STPs 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. More comprehensive and patient/pathway focussed analyses will be available when primary care data is linked in. 23. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed. 24. 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. 25. Provision of indicators of health problems, and patterns of risk within the commissioning region. 26. Support of benchmarking for evaluating progress in future years.

Benefits reported

Not stated in the previous version; added here.

The previous approval which permitted South Warwickshire CCG to analyse secondary care data linked to primary care (GP) data, provided significant benefit because the dataset was richer and enabled South Warwickshire CCG to analyse the full patient pathway across secondary care and primary care. For example, when they wanted to analyse the impact of projects that they have trialled where additional resources had been commissioned for specific cohorts of patients versus the pathway of patients who did not benefit from additional resources; they were able to more accurately evidence the benefit to the patients because of the richer dataset and were able then to justify funding wider roll-out of new services; or in some cases they were able to establish that the additional funding was not having the desired impact and enabled them to adjust the commissioned services.

However, the CCG’s ability to utilise the previous approval was limited because of their own lack of resource. The STP CCGs recognise that they can make even greater use of the combined secondary and primary care datasets by utilizing the resource and skills of the two new data processors (South Warwickshire NHS Foundation Trust and South Warwickshire GP Federation Ltd (SWGP). In addition the larger STP footprint will enable better pathway analysis as it allows more benchmarking and comparisons to be made across the region to better understand the population’s needs.

This is particularly pertinent following the coronavirus pandemic where prioritisation for restoration of services will be required as soon as possible and access to the data by both SWFT and the GP Federation to support the CCGs will aid restoration across the system and expedite this process. This will enable identification of the most at risk patients and target contact and intervention across the whole pathway – from out of hospital community, and primary care and acute secondary care.

DARS-NIC-238282-X0B6H-v1.5 1 June 2019 to 31 May 2022
Title
3 CCGs within Coventry and Warwickshire STP - Comm, including GP data
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 Sustainability Transformation Partnership (STP) area, which includes the following CCGs:

- NHS Coventry and Rugby CCG

- NHS South Warwickshire CCG

- NHS Warwickshire North 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 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 Sets (CRD) (Births and Deaths)

• Patient Reported Outcome Measures Data Set (PROMs)

• National Diabetes Audit Data Set (NDA)

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 CCGs wish to include pseudonymised primary care data in the population health management and patient stratification analyses to enable more comprehensive and patient/pathway focussed analyses.

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.

Patient data historically sits in silos within various NHS services. Linking datasets including GP data enables commissioners to fully understand the effective delivery of health and social care services for the populations they manage and not just for those directly receiving treatment. It supports commissioners to allocate resources as well as providing greater insight into the provision of services and to the health of the population.

Linking primary, secondary data supports with understanding a full patient’s journey across their pathway and across the community which can provide opportunities for understanding health needs pre and post treatment across numerous health services.

For example, analysis has shown that those able to manage their health conditions (GP data) are less likely to attend A&E and less likely to be admitted in an emergency (secondary care data). It can also support with coordinating discharge planning and integration of services as those receiving social care can be a key driver of demand for health and care.

Processing for commissioning, including the pseudo at source processing for patient stratification and population health management will be conducted by NHS Arden and GEM Commissioning Support Unit.

NHS Arden and GEM Commissioning Support Unit are the primary data processor for the three CCGs. NHS Arden and GEM Commissioning Support Unit use IT support services provided by NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by NHS Oldham CCG) and therefore both organisations are listed within the agreement as data processors although they only support the IT systems and do not access data.

The three CCGs are data controllers, but are listed as data processors in addition as processing occurs on the data the CCGs receive. The three CCGs use IT support services provided by Coventry and Warwickshire NHS Partnership Trust and therefore are listed within the agreement as data processor although they only support the IT systems and do not access 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:

a. Patients at highest risk of admission

b. Most expensive patients (top 15%)

c. Frail and elderly

d. Patients that are currently in hospital

e. Patients with most referrals to secondary care

f. Patients with most emergency activity

g. Patients with most expensive prescriptions

h. Patients recently moving from one care setting to another

i. Discharged from hospital

ii. Discharged from community

13. Profiling population health and wider determinants to identify and target those most in need

a. Understanding population profile and demographics

b. Identify patient cohorts with specific needs or who may benefit from interventions

c. Identifying disease prevalence. health and care needs for population cohorts

d. Contributing to Joint Strategic Needs Assessment (JSNA)

e. Geographical mapping and analysis

14. Identifying and managing preventable and existing conditions

a. Identifying types of individuals and population cohorts at risk of non-elective re-admission

b. Patient stratification to identify populations suitable for case management

c. Risk profiling and predictive modelling

d. Patient stratification for planning services for population cohorts

e. Identification of disease incidence and diagnosis stratification

15. 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

16. 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

17. Care co-ordination and planning

a. Planning packages of care

b. Service planning

c. Planning care co-ordination

18. 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 services to react to terror situations

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 New Models of Care (NMOC), Accountable Care Organisations (ACO), Sustainable Transformation Partnerships (STP)

i. Identifying duplications in care

j. Identifying gaps in care, missed diagnoses and triple fail events

k. Analysing individual and aggregated timelines

19. 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

20. 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

21. 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

22. Comparing expected levels

a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations

23. Comparing local targets & plan

a. Monitoring of local variation in productivity, cost, outcomes, quality and experience

b. Local performance dashboards by service provider, commissioner, geography, NMOC, STPs

24. Monitoring activity and cost compliance against contract and agreed plans

a. Contract monitoring

b. Contract reconciliation and challenge

c. Invoice validation

25. 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

26. Improving provider data quality

a. Coding audit

b. Data quality validation and review

c. Checking validity of patient identity and commissioner assignment

27. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.

28. 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.

29. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.

30. Understanding where patients 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.

31. Removal of patients from Risk Stratification reports.

32. 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.

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.

Cite this page

NHS England (2026) Data Uses Register, September 2026 edition, agreement DARS-NIC-238282-X0B6H, “3 CCGs within Coventry and Warwickshire STP - Comm, including GP data”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-238282-x0b6h/ (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-238282-X0B6H to see the original rows.