DSfC - NHS Northamptonshire CCG - RS, COMM & IV
NHS Northamptonshire ICB · Sub ICB Location
Listed under NHS Northamptonshire Integrated Care Board.
Expired The latest version ended on 16 March 2025. The September 2026 register still lists the agreement, but its term has passed.
- Reference
- DARS-NIC-362252-M1X0V
- Latest version
- v5.2
- Term of latest version
- 17 March 2022 to 16 March 2025
- Start date
- 1 April 2020
- Data controller
- Sole Data Controller
- Commercial purposes
- No
- Sublicensing
- No
- Files released to date
- 0
Why the data was released
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and NHS Northamptonshire CCG.
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Prescribing Services Ltd.
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 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)
- Medicines Dispensed in Primary Care (NHSBSA Data)
- Adult Social Care Data
Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
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.
Provide intelligence about the safety and effectiveness of medicines.
Allow analysis of patient pathways across healthcare and social care.
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 NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit, NHS Arden and Greater East Midlands Commissioning Support Unit, Optum Health Solutions (UK) Limited, NHS North East London CCG & NHS South West London CCG.
NHS Arden and Greater East Midlands Commissioning Support Uni are absorbing the functions of NHS North East London / North of England Commissioning Support Unit. Therefore there will be a period of dual running while the services are transitioned over.
Following the decommission of NHS North and East London Commissioning Support Unit (NEL CSU), the following CCGs have absorbed the responsibilities and staff members of the CSU:
- NHS South West London CCG
- NHS North East London CCG
The CCGs listed here will fulfil CSU responsibilities, processing data for the purposes listed within the Processing Activities below.
Optum's analyses of data aims to understand the needs of the population through whole population segmentation. This focuses on the entirety of the Primary Care Networks or Place/Integrated Care Partnership population and differentiates it into segments using a complexity measure and age. Further analyses are presented that stratify individuals in segments according to the presence or risk of poor outcomes. Places/Integrated Care Partnerships and Primary Care Networks have full autonomy to delve into any of the segments to identify cohorts for proactive intervention. Groups of patients of c.100-200 will be identified and pseudonymised NHS numbers passed from Optum to North and East London Commissioning Support Unit/ North of England Commissioning Support Unit / NHS Arden and Greater East Midlands Commissioning Support Unit support team for reports to be created for GPs with Role Based Access Controls and a legitimate caring relationship with the patients to identify individuals for intervention. Only those who already have a right to access this data e.g. for direct care purposes will be able to view this 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 DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.
ONWARD SHARING:
In the development of cohorts of pseudonymised patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct health or care professionals for the purpose of direct care. Additionally clinicians, made aware of a number of cases that they believe would need intervention may request re-identification for that direct care purpose. These instances of re-identification will generally be carried out as programmes of work or, rarely, on an individual/small group basis.
NHS Digital provides a re-identification service for this process. All re-id requests will be processed and authorised by NHS Digital on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.
The following are typical examples of instances where a CCG might want to use the re-identification process:
A&E High Attendance usage
The CCG can filter data to show for example the number of A&E attendances in a given period for each patient. The CCG can then flag to the relevant GP of the patient any patients that require intervention. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk.
Polypharmacy re-IDs
CCGs can request re-ID of a list of patients to be sent to the relevant GP with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.
The Re-identification process for direct care is as follows:
1. The CCG identifies a patient cohort to be re-identified for the purpose of direct care.
2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSU’s Business Intelligence (BI) Tool, or through a manual form.
3. The DSCRO assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system.
4. For automated systems, steps 1 - 3 wouldn’t apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without further checks.
5. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or Care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
6. DSCROs retain an audit trail of all re-id requests
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.
Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.
All access to data is auditable by NHS Digital.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.
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 the NHS Northamptonshire CCG region (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where NHS Northamptonshire 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 Northamptonshire CCG - this is only for commissioning and relates to both national and local flows.
and/or
• Patients treated by a provider where the NHS Northamptonshire CCG has joint responsibility for the provider services in the local health economy – this is only for Ambulance Trust data
For the purpose of Risk Stratification:
• Patients who are normally registered and/or resident within the NHS Northamptonshire CCG region (including historical activity where the patient was previously registered or resident in another commissioner
For the purpose of Invoice Validation:
• Patients who are resident and/or registered within the CCG region.
This includes data that was previously under a different organisation name but has now merged into this CCG
In addition to the dissemination of Cancer Waiting Times Data via the 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 Limited supply Cloud Services for NHS North and East London Commissioning Support Unit/North of England Commissioning Support Unit/Arden and GEM Commissioning Support Unit and Optum Health Solutions (UK) 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.
Amazon Web Services supply Cloud services to Optum Health Solutions UK 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.
NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by Northern Care Alliance NHS Foundation Trust) 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.
Interxion, The Bunker Secure Hosting Ltd, Ark Data Centres, Barking Havering and Redbridge Hospitals NHS Trust, Pulsant, IT Professional Services Ltd, 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.
INVOICE VALIDATION
North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit
1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit.
3. The CEfF also receive backing data from the provider.
4. North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes:
a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.
b. Once the provider backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit CEfF team and the provider, meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.
INVOICE VALIDATION
NHS Northamptonshire CCG
1. Identifiable SUS+ data is obtained by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) located in the CCG.
3. The CEfF also receive backing data from the provider.
4. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.
b. Once the provider backing information is received, it will be checked against national NHS and local commissioning policies, as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. In relation to a patient registered with the CCG, GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved.
RISK STRATIFICATION
NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit
1. Identifiable SUS+ and MHSDS data is transferred from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit, who securely hold the SUS+ and MHSDS data.
3. Identifiable GP Data is securely sent from the GP system to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit have completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
Prescribing Services Ltd:
1. Identifiable SUS+ data is transferred from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to Prescribing Services Ltd, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd have completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
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)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
20. Adult Social Care Data
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG
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), National Diabetes Audit (NDA) Patient Reported Outcome Measures (PROMs), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data only is securely transferred from the DSCRO to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG.
2. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG also receive GP data directly from providers (see points i – viii)
3. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG add derived fields by using existing data, 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
4. Allowed linkage is between the data sets contained within points 1& 2.
5. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG then pass the processed, pseudonymised and linked data to the Data Controller.
6. Aggregation of required data for CCG management use will be completed by NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG or the CCG as instructed by the Data Controller.
7. Patient level data will not be shared outside of the Data Controller and will only be shared within the Data Controller 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.
GP Data
NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG have individual data processing agreements in place with GPs to pseudonymise data. Acting on their behalf, they pseudonymise the data as follows:
i. Identifiable GP data is submitted to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG.
ii. The data lands in a ring-fenced area.
iii. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG has access to a pseudonymisation tool. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG requests an organisation specific pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the individual request and the organisation it is being requested for.
iv. The data is then pseudonymised using the organisation specific pseudonymisation tool and DSCRO issued key. The identifiable data is then deleted from the ring-fenced area.
v. To enable linkage to data listed in point 1, NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG make a request to the DSCRO.
vi. The DSCRO then send a mapping table to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG.
vii. A black box uses the mapping table to overwrite the organisation specific pseudonym with the DSCRO pseudonym to enable linkage to NHS Digital released products (under this agreement).
viii. The mapping table is then deleted.
Data Processor 2 - Optum Health Solutions (UK) Limited
1.NHS Northamptonshire CCG securely pass pseudonymised SUS, Community Services Data Set (CSDS), Mental Health Services Data Set, Local Provider data and GP Primary Care data only to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national data sets and sent as individual data flows.
2. Optum Health Solutions (UK) Ltd provide analysis to:
a. Whole population segmentation to assess population health needs
b. Prospective risk scoring for individuals at risk and an understanding of the drivers of the risk
c. Predictive modelling to determine individuals at risk and an understanding of the drivers of the risk
d. Longitudinal analysis of intersegmental drift - identifying individuals who move between complexity classifications and the drivers of these transitions
e. The production of individual level theographs to identify gaps in care.
3. Allowed linkage is between the datasets contained within point (1) above. GP data, CSDS and Mental Health Services datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.
4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG (this may be via the CSU).
5. Aggregated required data for CCG Management use will be completed by Optum Health Solutions (UK) Ltd or to the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis as per the purposes stipulated with 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 dataset.
7. Optum Health Solutions (UK) Ltd will only be in receipt of data and only be permitted to act as Data Processors for the period specified in the contract with the CCG.
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
5. Support validating financial payments for contracted and non-contracted activity, determining if the CCG is the responsible commissioner for the patient.
RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify cohorts of patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
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 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. The identification of variation in quality of services and potential efficiencies across pathways
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. In improving the quality of referrals under current structures, CCGs are able to monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. CCGs may 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. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able 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.
23. Allow Commissioners to better protect or improve the public health of the total local patient population.
24. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population.
25. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
26. Linking prescribing habits to entry points into the health and social care system
27. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care
30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
Expected measurable benefits
INVOICE VALIDATION
The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by:
1. Ensuring that activity is fully financially validated.
2. Ensuring that service providers are accurately paid for the patients treatment.
3. Enabling services to be planned, commissioned, managed, and subjected to financial control.
4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they are responsible.
5. Fulfilling commissioners duties to fiscal probity and scrutiny.
6. Ensuring full financial accountability for relevant organisations.
7. Ensuring robust commissioning and performance management.
8. Ensuring commissioning objectives do not compromise patient confidentiality.
9. Ensuring the avoidance of misappropriation of public funds.
RISK STRATIFICATION
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early intervention.
3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care.
5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes
6. Enables GPs to better target mental health care intervention
All of the above lead to improved patient experience and health outcomes through more effective commissioning of services.
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.
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
20. Help drive changes in healthcare
21. Allows comparisons of providers performance to assist improvement in services – increase the quality
22. Inform commissioners and improve services
23. 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.
24. Understanding the interdependency of care services
25. Targeting care more effectively
26. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
27. 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
28. 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
29. Service redesign
30. Health Needs Assessment – identification of underlying disease prevalence within the local population
31. 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).
32. Support the Age Well agenda through the rapid transformation of services across multiple providers through co-production of targeted interventions across systems and pathways.
33. Monitoring of entire population, as a opposed to only those that engage with services.
34. 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.
35. Monitor the quality and safety of the delivery of healthcare services.
36. Allow focused commissioning support based on factual data rather than assumed and projected sources.
37. By adopting a Population Health Management approach using Optum of data driven planning and delivery of care, support and services can be appropriately targeted to improve residents physical and mental health outcomes and overall wellbeing, whilst reducing health inequalities within and across Northamptonshire.
38. Understand admissions linked to overprescribing.
39. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
40. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
41. Designing and implementing new payment models across health and adult social care
42. Understanding current and future population needs and resource utilisation for local strategic planning and commissioning purposes including for health, social care and public health needs.
Benefits reported so far
NHS Northamptonshire CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. NHS Northamptonshire CCG will use intelligence to add insight to strategic commissioning and service integration across Northamptonshire. This work will continue year on year to match the delivery/funding of targets services for the population.
The CCG does publish an annual report on their website - https://www.northamptonshireccg.nhs.uk/about/annual-reports.htm - which includes a summary of the recent achievements and benefits realised, for which use of NHS Digital data supports.
Datasets on the latest version
Legal basis for provision: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.
| Dataset | Type of data | Sensitivity | Frequency | Confidential data |
|---|---|---|---|---|
| Acute-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Adult Social Care | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Ambulance-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Children and Young People Health | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Civil Registration - Births | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Civil Registrations of Death | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Community Services Data Set (CSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Community-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Demand for Service-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Diagnostic Imaging Data Set (DID) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Diagnostic Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| e-Referral Service for Commissioning | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Emergency Care-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Experience, Quality and Outcomes-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Improving Access to Psychological Therapies (IAPT) v1.5 | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Maternity Services Data Set | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Medicines dispensed in Primary Care (NHSBSA data) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health and Learning Disabilities Data Set (MHLDDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health Minimum Data Set (MHMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health Services Data Set (MHSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health Services Data Set (MHSDS) | Identifiable | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Mental Health-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| National Diabetes Audit | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Patient Reported Outcome Measures (PROMs) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Personal Demographic Service | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Population Data-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Primary Care Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Public Health and Screening Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| Summary Hospital-level Mortality Indicator (SHMI) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| SUS for Commissioners | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
| SUS for Commissioners | Identifiable | Sensitive | Frequent Adhoc Flow | Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s) |
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 6 versions.
DARS-NIC-362252-M1X0V-v5.2 17 March 2022 to 16 March 2025
- Title
- DSfC - NHS Northamptonshire CCG - RS, COMM & IV
- Commercial
- No
- Sublicensing
- No
- Datasets
- 33
- Files released
- 0
Datasets: Acute-Local Provider Flows; Adult Social Care; 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; Medicines dispensed in Primary Care (NHSBSA data); Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); 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; SUS for Commissioners
What changed from DARS-NIC-362252-M1X0V-v4.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2022-03-17 | |
| End date | 2025-03-16 |
Objective for processing
[63 paragraphs unchanged]
Processing for commissioning will be conducted by NHS North and East London
[6 words unchanged]
England Commissioning Support Unit, NHS Arden and Greater East Midlands Commissioning Support
Unit and
Unit,
Optum Health Solutions (UK)
Limited.
Limited, NHS North East London CCG & NHS South West London CCG.
[1 paragraph unchanged]
Following the decommission of NHS North and East London Commissioning Support Unit (NEL CSU), the following CCGs have absorbed the responsibilities and staff members of the CSU:
- NHS South West London CCG
- NHS North East London CCG
The CCGs listed here will fulfil CSU responsibilities, processing data for the purposes listed within the Processing Activities below.
[1 paragraph unchanged]
Processing activities
[51 paragraphs unchanged]
Interxion, The Bunker Secure Hosting Ltd and Ark Data Centres 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.
[1 paragraph unchanged]
Interxion, The Bunker Secure Hosting Ltd, Ark Data Centres, Barking Havering and Redbridge Hospitals NHS Trust, Pulsant, IT Professional Services Ltd,
Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust)
[39 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
Pulsant and IT Professional Services Ltd 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.
[74 paragraphs unchanged]
Data Processor 1 – NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[88 words unchanged]
of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit.
Unit/NHS North East London CCG/NHS South West London CCG.
2. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
also receive GP data directly from providers (see points i – viii)
3. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
add derived fields by using existing data, link data and provide analysis to:
[8 paragraphs unchanged]
5. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
then pass the processed, pseudonymised and linked data to the
CCG.
Data Controller.
6. Aggregation of required data for CCG management use will be completed
[10 words unchanged]
of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
or the CCG as instructed by the
CCG.
Data Controller.
7. Patient level data will not be shared outside of the
CCG
Data Controller
and will only be shared within the
CCG
Data Controller
on a need to know basis, as per the purposes stipulated within
[15 words unchanged]
as set out within NHS Digital guidance applicable to each data set.
[1 paragraph unchanged]
NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
have individual data processing agreements in place with GPs to pseudonymise data. Acting on their behalf, they pseudonymise the data as follows:
i. Identifiable GP data is submitted to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit.
Unit/NHS North East London CCG/NHS South West London CCG.
[1 paragraph unchanged]
iii. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
has access to a pseudonymisation tool. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
requests an organisation specific pseudonymisation key from the DSCRO. The key can
[8 words unchanged]
to the individual request and the organisation it is being requested for.
[1 paragraph unchanged]
v. To enable linkage to data listed in point 1, NHS North
[7 words unchanged]
of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
make a request to the DSCRO.
vi. The DSCRO then send a mapping table to NHS North and
[6 words unchanged]
of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit.
Unit/NHS North East London CCG/NHS South West London CCG.
[15 paragraphs unchanged]
Expected measurable benefits
[62 paragraphs unchanged]
26. Using value as the redesign principle
26. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
27. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
27. 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
28. 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
28. 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
29. 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
29. Service redesign
30. Service redesign
30. Health Needs Assessment – identification of underlying disease prevalence within the local population
31. Health Needs Assessment – identification of underlying disease prevalence within the local population
31. 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).
32. 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).
32. Support the Age Well agenda through the rapid transformation of services across multiple providers through co-production of targeted interventions across systems and pathways.
33. Support the Age Well agenda through the rapid transformation of services across multiple providers through co-production of targeted interventions across systems and pathways.
33. Monitoring of entire population, as a opposed to only those that engage with services.
34. Monitoring of entire population, as a opposed to only those that engage with services.
34. 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.
35. 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.
35. Monitor the quality and safety of the delivery of healthcare services.
36. Monitor the quality and safety of the delivery of healthcare services.
36. Allow focused commissioning support based on factual data rather than assumed and projected sources.
37. Allow focused commissioning support based on factual data rather than assumed and projected sources.
37. By adopting a Population Health Management approach using Optum of data driven planning and delivery of care, support and services can be appropriately targeted to improve residents physical and mental health outcomes and overall wellbeing, whilst reducing health inequalities within and across Northamptonshire.
38. By adopting a Population Health Management approach using Optum of data driven planning and delivery of care, support and services can be appropriately targeted to improve residents physical and mental health outcomes and overall wellbeing, whilst reducing health inequalities within and across Northamptonshire.
38. Understand admissions linked to overprescribing.
39. Understand admissions linked to overprescribing.
39. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
40. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
40. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
41. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
41. Designing and implementing new payment models across health and adult social care
42. Designing and implementing new payment models across health and adult social care
42. Understanding current and future population needs and resource utilisation for local strategic planning and commissioning purposes including for health, social care and public health needs.
43. Understanding current and future population needs and resource utilisation for local strategic planning and commissioning purposes including for health, social care and public health needs.
Unchanged: Expected output, Benefits reported.
DARS-NIC-362252-M1X0V-v4.2 24 January 2022 to 23 January 2025
- Title
- DSfC - NHS Northamptonshire CCG - RS, COMM & IV
- Commercial
- No
- Sublicensing
- No
- Datasets
- 33
- Files released
- 0
Datasets: Acute-Local Provider Flows; Adult Social Care; 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; Medicines dispensed in Primary Care (NHSBSA data); Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); 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; SUS for Commissioners
What changed from DARS-NIC-362252-M1X0V-v3.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2022-01-24 | |
| End date | 2025-01-23 |
Objective for processing
[4 paragraphs unchanged]
Invoice Validation will be conducted by NHS North and East London Commissioning Support
Unit and
Unit,
NHS North of England Commissioning Support
Unit.
Unit and NHS Northamptonshire CCG.
[58 paragraphs unchanged]
Processing for commissioning will be conducted by NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support
Unit, NHS Arden and Greater East Midlands Commissioning Support
Unit and Optum Health Solutions (UK) Limited.
Optum's analyses of data aims to understand the needs of the population through whole population segmentation. This focuses on the entirety of the Primary Care Networks or Place/Integrated Care Partnership population and differentiates it into segments using a complexity measure and age. Further analyses are presented that stratify individuals in segments according to the presence or risk of poor outcomes. Places/Integrated Care Partnerships and Primary Care Networks have full autonomy to delve into any of the segments to identify cohorts for proactive intervention. Groups of patients of c.100-200 will be identified and pseudonymised NHS numbers passed from Optum to North and East London Commissioning Support Unit/ North of England Commissioning Support Unit support team for reports to be created within North and East London Commissioning Support Unit/ North of England Commissioning Support Unit tooling for GPs with Role Based Access Controls and a legitimate caring relationship with the patients to identify individuals for intervention. Only those who already have a right to access this data e.g. for direct care purposes will be able to view this data.
NHS Arden and Greater East Midlands Commissioning Support Uni are absorbing the functions of NHS North East London / North of England Commissioning Support Unit. Therefore there will be a period of dual running while the services are transitioned over.
Optum's analyses of data aims to understand the needs of the population through whole population segmentation. This focuses on the entirety of the Primary Care Networks or Place/Integrated Care Partnership population and differentiates it into segments using a complexity measure and age. Further analyses are presented that stratify individuals in segments according to the presence or risk of poor outcomes. Places/Integrated Care Partnerships and Primary Care Networks have full autonomy to delve into any of the segments to identify cohorts for proactive intervention. Groups of patients of c.100-200 will be identified and pseudonymised NHS numbers passed from Optum to North and East London Commissioning Support Unit/ North of England Commissioning Support Unit / NHS Arden and Greater East Midlands Commissioning Support Unit support team for reports to be created for GPs with Role Based Access Controls and a legitimate caring relationship with the patients to identify individuals for intervention. Only those who already have a right to access this data e.g. for direct care purposes will be able to view this data.
Processing activities
[10 paragraphs unchanged]
The data will flow from NEL DSCRO to NEL CSU data warehouse where it will remain in a secure logically segregated location.
[1 paragraph unchanged]
There is no requirement for the analytical teams to re-identify patients, but in
In
the development of cohorts of
pseudonymised
patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct
healthcare
health or care
professionals
or local authority direct care staff only
for the purpose of direct care.
All re-id requests will be processed and authorised by the DSCRO on
Additionally clinicians, made aware of
a
case by case basis. National data opt outs are not applied in these
number of
cases
as
that
they
are
believe would need intervention may request re-identification
for
the purposes of
that
direct care
which follows the legal basis
purpose. These instances
of
implied consent.
re-identification will generally be carried out as programmes of work or, rarely, on an individual/small group basis.
An example of a request for the re-id of patients for direct care may be;
NHS Digital provides a re-identification service for this process. All re-id requests will be processed and authorised by NHS Digital on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.
The following are typical examples of instances where a CCG might want to use the re-identification process:
[3 paragraphs unchanged]
CCG's
CCGs
can request re-ID of a list of patients to be sent to
[37 words unchanged]
A by-product of such reviews may be to reduce costs of medication.
[1 paragraph unchanged]
1. The CCG identifies a patient cohort
(typically small numbers)
to be re-identified for the purpose of direct care.
[1 paragraph unchanged]
3. The DSCRO
(either through an automated system or manual checking in line with the request)
assesses as to whether the request passes the specified re-identification process checks.
[35 words unchanged]
for example around timings and the requestor’s relationship with patients in the
data
data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system.
4. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
4. For automated systems, steps 1 - 3 wouldn’t apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without further checks.
5. DSCROs retain an audit trail of all re-id requests
5. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or Care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
6. National Data opt outs are not applied for the purpose of direct care
6. DSCROs retain an audit trail of all re-id requests
[14 paragraphs unchanged]
and/or
• Patients treated by a provider where the NHS Northamptonshire CCG has joint responsibility for the provider services in the local health economy – this is only for Ambulance Trust data
[8 paragraphs unchanged]
Microsoft Limited supply Cloud Services for NHS North and East London Commissioning Support Unit/North of England
Commissioning Support Unit/Arden and GEM
Commissioning Support Unit and Optum Health Solutions (UK) Limited and are therefore
[33 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[2 paragraphs unchanged]
NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by Northern Care Alliance NHS Foundation Trust) 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.
Pulsant and IT Professional Services Ltd 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.
[1 paragraph unchanged]
North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit
[1 paragraph unchanged]
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the North East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit.
[8 paragraphs unchanged]
INVOICE VALIDATION
NHS Northamptonshire CCG
1. Identifiable SUS+ data is obtained by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) located in the CCG.
3. The CEfF also receive backing data from the provider.
4. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.
b. Once the provider backing information is received, it will be checked against national NHS and local commissioning policies, as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. In relation to a patient registered with the CCG, GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved.
[1 paragraph unchanged]
NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support
Unit:
Unit
[1 paragraph unchanged]
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to
NHS
North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit, who securely hold the SUS+ and MHSDS data.
3. Identifiable GP Data is securely sent from the GP system to
NHS
North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit.
[2 paragraphs unchanged]
6. Once
NHS
North and East London Commissioning Support Unit/NHS North of England Commissioning Support
[12 words unchanged]
via a secure connection to access the data pseudonymised at patient level.
[42 paragraphs unchanged]
Data Processor 1 – NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support
Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[67 words unchanged]
Adult Social Care data only is securely transferred from the DSCRO to
NHS
North
and
East London Commissioning Support Unit/NHS North of England Commissioning Support
Unit/NHS Arden and Greater East Midlands Commissioning Support
Unit.
2.North
2. NHS North and
East London Commissioning Support Unit/NHS North of England
Commissioning Support Unit/NHS Arden and Greater East Midlands
Commissioning Support Unit also receive GP data directly from providers (see points i –
iii)
viii)
3.
NHS
North
and
East London Commissioning Support Unit/NHS North of England
Commissioning Support Unit/NHS Arden and Greater East Midlands
Commissioning Support Unit add derived fields by using existing data, link data and provide analysis to:
[7 paragraphs unchanged]
3.
4.
Allowed linkage is between the data sets contained within points 1& 2.
4.
5. NHS
North and East London Commissioning Support Unit/NHS North of England
Commissioning Support Unit/NHS Arden and Greater East Midlands
Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG.
5.
6.
Aggregation of required data for CCG management use will be completed by
NHS
North
and
East London
Commissioning//NHS
Commissioning Support Unit/NHS
North of England Commissioning Support
Unit
Unit/NHS Arden and Greater East Midlands Commissioning
Support Unit or the CCG as instructed by the CCG.
6.
7.
Patient level data will not be shared outside of the CCG and
[34 words unchanged]
as set out within NHS Digital guidance applicable to each data set.
[1 paragraph unchanged]
i. Identifiable GP data is extracted from consented GP practices Principal Clinical System via NEL-hosted IM1 GP Extraction service.
NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit have individual data processing agreements in place with GPs to pseudonymise data. Acting on their behalf, they pseudonymise the data as follows:
ii. Extracted data lands on secure NEL CSU/NECS CSU GP Environment where strict access is limited to individuals who have been authorised by NEL DSCRO Business Lead or Senior Information Risk Owner and act on behalf of the Data Controller (GP Practice).
i. Identifiable GP data is submitted to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit.
iii. The NEL CSU/NECS CSU Pseudonym is then applied to GP data within Secure GP Data Environment via a Black Box function. The pseudonymisation enables the linkage with other data sets specified in this DSA.
ii. The data lands in a ring-fenced area.
iii. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit has access to a pseudonymisation tool. NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit requests an organisation specific pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the individual request and the organisation it is being requested for.
iv. The data is then pseudonymised using the organisation specific pseudonymisation tool and DSCRO issued key. The identifiable data is then deleted from the ring-fenced area.
v. To enable linkage to data listed in point 1, NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit make a request to the DSCRO.
vi. The DSCRO then send a mapping table to NHS North and East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS Arden and Greater East Midlands Commissioning Support Unit.
vii. A black box uses the mapping table to overwrite the organisation specific pseudonym with the DSCRO pseudonym to enable linkage to NHS Digital released products (under this agreement).
viii. The mapping table is then deleted.
[13 paragraphs unchanged]
Benefits reported
[1 paragraph unchanged] The CCG does publish an annual report on their website - https://www.northamptonshireccg.nhs.uk/about/annual-reports.htm - which includes a summary of the recent achievements and benefits realised, for which use of NHS Digital data supports.
Unchanged: Expected output, Expected measurable benefits.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and NHS Northamptonshire CCG.
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Prescribing Services Ltd.
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 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)
- Medicines Dispensed in Primary Care (NHSBSA Data)
- Adult Social Care Data
Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
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.
Provide intelligence about the safety and effectiveness of medicines.
Allow analysis of patient pathways across healthcare and social care.
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 NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit, NHS Arden and Greater East Midlands Commissioning Support Unit and Optum Health Solutions (UK) Limited.
NHS Arden and Greater East Midlands Commissioning Support Uni are absorbing the functions of NHS North East London / North of England Commissioning Support Unit. Therefore there will be a period of dual running while the services are transitioned over.
Optum's analyses of data aims to understand the needs of the population through whole population segmentation. This focuses on the entirety of the Primary Care Networks or Place/Integrated Care Partnership population and differentiates it into segments using a complexity measure and age. Further analyses are presented that stratify individuals in segments according to the presence or risk of poor outcomes. Places/Integrated Care Partnerships and Primary Care Networks have full autonomy to delve into any of the segments to identify cohorts for proactive intervention. Groups of patients of c.100-200 will be identified and pseudonymised NHS numbers passed from Optum to North and East London Commissioning Support Unit/ North of England Commissioning Support Unit / NHS Arden and Greater East Midlands Commissioning Support Unit support team for reports to be created for GPs with Role Based Access Controls and a legitimate caring relationship with the patients to identify individuals for intervention. Only those who already have a right to access this data e.g. for direct care purposes will be able to view this data.
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
5. Support validating financial payments for contracted and non-contracted activity, determining if the CCG is the responsible commissioner for the patient.
RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify cohorts of patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
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 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. The identification of variation in quality of services and potential efficiencies across pathways
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. In improving the quality of referrals under current structures, CCGs are able to monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. CCGs may 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. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able 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.
23. Allow Commissioners to better protect or improve the public health of the total local patient population.
24. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population.
25. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
26. Linking prescribing habits to entry points into the health and social care system
27. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care
30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
Benefits reported
NHS Northamptonshire CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. NHS Northamptonshire CCG will use intelligence to add insight to strategic commissioning and service integration across Northamptonshire. This work will continue year on year to match the delivery/funding of targets services for the population.
The CCG does publish an annual report on their website - https://www.northamptonshireccg.nhs.uk/about/annual-reports.htm - which includes a summary of the recent achievements and benefits realised, for which use of NHS Digital data supports.
DARS-NIC-362252-M1X0V-v3.3 10 October 2021 to 9 October 2024
- Title
- DSfC - NHS Northamptonshire CCG - RS, COMM & IV
- Commercial
- No
- Sublicensing
- No
- Datasets
- 33
- Files released
- 0
Datasets: Acute-Local Provider Flows; Adult Social Care; 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; Medicines dispensed in Primary Care (NHSBSA data); Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); 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; SUS for Commissioners
What changed from DARS-NIC-362252-M1X0V-v2.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2021-10-10 | |
| End date | 2024-10-09 |
Datasets: + Adult Social Care
Objective for processing
[4 paragraphs unchanged]
Invoice Validation will be conducted by NHS North and East London Commissioning Support Unit
and NHS North of England Commissioning Support Unit.
[3 paragraphs unchanged]
Risk Stratification will be conducted by NHS North and East London Commissioning Support
Unit, NHS North of England Commissioning Support
Unit and Prescribing Services Ltd.
[35 paragraphs unchanged]
- Adult Social Care Data
Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.
[4 paragraphs unchanged]
• Using value as the redesign principle
[11 paragraphs unchanged]
Allow analysis of patient pathways across healthcare and social care.
[1 paragraph unchanged]
Processing for commissioning will be conducted by NHS North and East London Commissioning Support
Unit, NHS North of England Commissioning Support
Unit and Optum Health Solutions (UK) Limited.
Optum's analyses of data aims to understand the needs of the population
[81 words unchanged]
NHS numbers passed from Optum to North and East London Commissioning Support
Unit/ North of England Commissioning Support
Unit support team for reports to be created within North and East London
Commissioning Support Unit/ North of England
Commissioning Support Unit tooling for GPs with Role Based Access Controls and
[23 words unchanged]
e.g. for direct care purposes will be able to view this data.
Processing activities
[12 paragraphs unchanged]
Patient level data will not be shared outside of the CCG 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.
There is no requirement for the analytical teams to re-identify patients, but in the development of cohorts of patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct healthcare professionals or local authority direct care staff only for the purpose of direct care. All re-id requests will be processed and authorised by the DSCRO on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.
An example of a request for the re-id of patients for direct care may be;
A&E High Attendance usage
The CCG can filter data to show for example the number of A&E attendances in a given period for each patient. The CCG can then flag to the relevant GP of the patient any patients that require intervention. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk.
Polypharmacy re-IDs
CCG's can request re-ID of a list of patients to be sent to the relevant GP with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.
The Re-identification process for direct care is as follows:
1. The CCG identifies a patient cohort (typically small numbers) to be re-identified for the purpose of direct care.
2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSU’s Business Intelligence (BI) Tool, or through a manual form.
3. The DSCRO (either through an automated system or manual checking in line with the request) assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data
4. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
5. DSCROs retain an audit trail of all re-id requests
6. National Data opt outs are not applied for the purpose of direct care
[22 paragraphs unchanged]
Microsoft Limited supply Cloud Services for NHS North and East London Commissioning Support
Unit/North of England Commissioning Support
Unit
and Optum Health Solutions (UK) Limited
and are therefore listed as a data processor. They supply support to
[24 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[6 paragraphs unchanged]
4. North East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes:
[5 paragraphs unchanged]
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between North East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit CEfF team and the provider, meaning that no identifiable
[16 words unchanged]
management reporting detailing the total quantum of invoices received pending, processed etc.
[1 paragraph unchanged]
NHS North and East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit:
[1 paragraph unchanged]
2. Data quality management and standardisation of data is completed by the
[9 words unchanged]
NHS number is transferred securely to North and East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit, who securely hold the SUS+ and MHSDS data.
3. Identifiable GP Data is securely sent from the GP system to North and East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit.
[2 paragraphs unchanged]
6. Once North and East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit have completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
[40 paragraphs unchanged]
20. Adult Social Care Data
[1 paragraph unchanged]
Data Processor 1 – NHS North and East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[46 words unchanged]
Reported Outcome Measures (PROMs), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator
(SHMI) and
(SHMI),
Medicines Dispensed in Primary Care (NHSBSA Data)
and Adult Social Care data only
is securely transferred from the DSCRO to North East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit.
2.North East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit also receive GP data directly from providers (see points i – iii)
3. North East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit add derived fields by using existing data, link data and provide analysis to:
[8 paragraphs unchanged]
4. North and East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregation of required data for CCG management use will be completed by North East London
Commissioning//NHS North of England
Commissioning
Support Unit
Support Unit or the CCG as instructed by the CCG.
[3 paragraphs unchanged]
ii. Extracted data lands on secure NEL
CSU/NECS
CSU GP Environment where strict access is limited to individuals who have
[10 words unchanged]
Risk Owner and act on behalf of the Data Controller (GP Practice).
iii. The NEL
CSU/NECS
CSU Pseudonym is then applied to GP data within Secure GP Data
[7 words unchanged]
pseudonymisation enables the linkage with other data sets specified in this DSA.
[1 paragraph unchanged]
1.NHS
South West London
Northamptonshire
CCG securely pass pseudonymised SUS, Community Services Data Set (CSDS), Mental Health
[22 words unchanged]
from the other national data sets and sent as individual data flows.
[11 paragraphs unchanged]
Expected output
[7 paragraphs unchanged] 5. Support validating financial payments for contracted and non-contracted activity, determining if the CCG is the responsible commissioner for the patient. [72 paragraphs unchanged] 28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy) 29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care 30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
Expected measurable benefits
[77 paragraphs unchanged] 41. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care 42. Designing and implementing new payment models across health and adult social care 43. Understanding current and future population needs and resource utilisation for local strategic planning and commissioning purposes including for health, social care and public health needs.
Unchanged: Benefits reported.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS North and East London Commissioning Support Unit and NHS North of England Commissioning Support Unit.
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Prescribing Services Ltd.
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 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)
- Medicines Dispensed in Primary Care (NHSBSA Data)
- Adult Social Care Data
Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
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.
Provide intelligence about the safety and effectiveness of medicines.
Allow analysis of patient pathways across healthcare and social care.
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 NHS North and East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Optum Health Solutions (UK) Limited.
Optum's analyses of data aims to understand the needs of the population through whole population segmentation. This focuses on the entirety of the Primary Care Networks or Place/Integrated Care Partnership population and differentiates it into segments using a complexity measure and age. Further analyses are presented that stratify individuals in segments according to the presence or risk of poor outcomes. Places/Integrated Care Partnerships and Primary Care Networks have full autonomy to delve into any of the segments to identify cohorts for proactive intervention. Groups of patients of c.100-200 will be identified and pseudonymised NHS numbers passed from Optum to North and East London Commissioning Support Unit/ North of England Commissioning Support Unit support team for reports to be created within North and East London Commissioning Support Unit/ North of England Commissioning Support Unit tooling for GPs with Role Based Access Controls and a legitimate caring relationship with the patients to identify individuals for intervention. Only those who already have a right to access this data e.g. for direct care purposes will be able to view this data.
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
5. Support validating financial payments for contracted and non-contracted activity, determining if the CCG is the responsible commissioner for the patient.
RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify cohorts of patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
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 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. The identification of variation in quality of services and potential efficiencies across pathways
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. In improving the quality of referrals under current structures, CCGs are able to monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. CCGs may 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. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able 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.
23. Allow Commissioners to better protect or improve the public health of the total local patient population.
24. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population.
25. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
26. Linking prescribing habits to entry points into the health and social care system
27. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care
30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
Benefits reported
NHS Northamptonshire CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. NHS Northamptonshire CCG will use intelligence to add insight to strategic commissioning and service integration across Northamptonshire. This work will continue year on year to match the delivery/funding of targets services for the population.
DARS-NIC-362252-M1X0V-v2.2 18 June 2021 to 17 June 2024
- Title
- DSfC - NHS Northamptonshire CCG - RS, COMM & IV
- Commercial
- No
- Sublicensing
- No
- Datasets
- 32
- 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; Medicines dispensed in Primary Care (NHSBSA data); Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); 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; SUS for Commissioners
What changed from DARS-NIC-362252-M1X0V-v1.4
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2021-06-18 | |
| End date | 2024-06-17 |
Datasets: + Medicines dispensed in Primary Care (NHSBSA data); + Personal Demographic Service; + Summary Hospital-level Mortality Indicator (SHMI)
Objective for processing
[4 paragraphs unchanged]
Invoice Validation will be conducted by
NHS
North
and
East London Commissioning Support Unit
[3 paragraphs unchanged]
Risk Stratification will be conducted by
NHS
North
and
East London Commissioning Support Unit and Prescribing Services Ltd.
[32 paragraphs unchanged]
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
[14 paragraphs unchanged]
Support measuring the health, mortality or care needs of the total local population.
Provide intelligence about the safety and effectiveness of medicines.
[1 paragraph unchanged]
Processing for commissioning will be conducted by
NHS
North
and
East London Commissioning Support
Unit.
Unit and Optum Health Solutions (UK) Limited.
Optum's analyses of data aims to understand the needs of the population through whole population segmentation. This focuses on the entirety of the Primary Care Networks or Place/Integrated Care Partnership population and differentiates it into segments using a complexity measure and age. Further analyses are presented that stratify individuals in segments according to the presence or risk of poor outcomes. Places/Integrated Care Partnerships and Primary Care Networks have full autonomy to delve into any of the segments to identify cohorts for proactive intervention. Groups of patients of c.100-200 will be identified and pseudonymised NHS numbers passed from Optum to North and East London Commissioning Support Unit support team for reports to be created within North and East London Commissioning Support Unit tooling for GPs with Role Based Access Controls and a legitimate caring relationship with the patients to identify individuals for intervention. Only those who already have a right to access this data e.g. for direct care purposes will be able to view this data.
Processing activities
[20 paragraphs unchanged]
This includes data that was previously under a different organisation name but has now merged into this CCG
[11 paragraphs unchanged]
This includes data that was previously under a different organisation name but has now merged into this CCG
[3 paragraphs unchanged]
Microsoft Limited supply
provide
Cloud Services for
NHS
North
and
East London Commissioning Support Unit and are therefore listed as a data
[29 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
Interxion
Amazon Web Services supply Cloud services to Optum Health Solutions UK Limited
and
Ark Data Centres
are therefore listed as a data processor. They supply support to the system, but
do not access
data held under this agreement as they only supply the building.
data.
Therefore, any access to the data held under this agreement would be
[5 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
Interxion, The Bunker Secure Hosting Ltd and Ark Data Centres 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.
[12 paragraphs unchanged]
NHS North and East London Commissioning Support Unit:
[1 paragraph unchanged]
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to North
and
East London Commissioning Support Unit, who securely hold the SUS+ and MHSDS data.
3. Identifiable GP Data is securely sent from the GP system to North
and
East London Commissioning Support
Unit and Prescribing Services Ltd.
Unit.
[2 paragraphs unchanged]
6. Once North
and
East London Commissioning Support Unit
and Prescribing Services Ltd
have completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
Prescribing Services Ltd:
1. Identifiable SUS+ data is transferred from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to Prescribing Services Ltd, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd have completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
[30 paragraphs unchanged]
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
[1 paragraph unchanged]
Data Processor 1 –
NHS
North
and
East London Commissioning Support Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[33 words unchanged]
(CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA)
and
Patient Reported Outcome Measures
(PROMs) only
(PROMs), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI) and Medicines Dispensed in Primary Care (NHSBSA Data)
is securely transferred from the DSCRO to North East London Commissioning Support Unit.
2. North East London Commissioning Support Unit add derived fields by using existing data, link data and provide analysis to:
2.North East London Commissioning Support Unit also receive GP data directly from providers (see points i – iii)
3. North East London Commissioning Support Unit add derived fields by using existing data, link data and provide analysis to:
[7 paragraphs unchanged]
3. Allowed linkage is between the data sets contained within
point 1.
points 1& 2.
4. North
and
East London Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG.
[2 paragraphs unchanged]
GP Data
i. Identifiable GP data is extracted from consented GP practices Principal Clinical System via NEL-hosted IM1 GP Extraction service.
ii. Extracted data lands on secure NEL CSU GP Environment where strict access is limited to individuals who have been authorised by NEL DSCRO Business Lead or Senior Information Risk Owner and act on behalf of the Data Controller (GP Practice).
iii. The NEL CSU Pseudonym is then applied to GP data within Secure GP Data Environment via a Black Box function. The pseudonymisation enables the linkage with other data sets specified in this DSA.
Data Processor 2 - Optum Health Solutions (UK) Limited
1.NHS South West London CCG securely pass pseudonymised SUS, Community Services Data Set (CSDS), Mental Health Services Data Set, Local Provider data and GP Primary Care data only to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national data sets and sent as individual data flows.
2. Optum Health Solutions (UK) Ltd provide analysis to:
a. Whole population segmentation to assess population health needs
b. Prospective risk scoring for individuals at risk and an understanding of the drivers of the risk
c. Predictive modelling to determine individuals at risk and an understanding of the drivers of the risk
d. Longitudinal analysis of intersegmental drift - identifying individuals who move between complexity classifications and the drivers of these transitions
e. The production of individual level theographs to identify gaps in care.
3. Allowed linkage is between the datasets contained within point (1) above. GP data, CSDS and Mental Health Services datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.
4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG (this may be via the CSU).
5. Aggregated required data for CCG Management use will be completed by Optum Health Solutions (UK) Ltd or to the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis as per the purposes stipulated with 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 dataset.
7. Optum Health Solutions (UK) Ltd will only be in receipt of data and only be permitted to act as Data Processors for the period specified in the contract with the CCG.
Expected output
[72 paragraphs unchanged] 23. Allow Commissioners to better protect or improve the public health of the total local patient population. 24. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population. 25. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 25. Investigate mortality outcomes for trusts. Identify medication prescribing trends and their effectiveness. 26. Linking prescribing habits to entry points into the health and social care system 27. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
Expected measurable benefits
[19 paragraphs unchanged] All of the above lead to improved patient experience and health outcomes through more effective commissioning of services. [50 paragraphs unchanged] 34. Monitoring of entire population, as a opposed to only those that engage with services. 35. 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. 36. Monitor the quality and safety of the delivery of healthcare services. 37. Allow focused commissioning support based on factual data rather than assumed and projected sources. 38. By adopting a Population Health Management approach using Optum of data driven planning and delivery of care, support and services can be appropriately targeted to improve residents physical and mental health outcomes and overall wellbeing, whilst reducing health inequalities within and across Northamptonshire. 39. Understand admissions linked to overprescribing. 40. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
Benefits reported
NHS Northamptonshire CCG will
look
to build on the yielded benefits of commissioning services that meet the needs of
our
their
local population, and that are effective in their delivery. NHS Northamptonshire CCG
[19 words unchanged]
on year to match the delivery/funding of targets services for the population.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS North and East London Commissioning Support Unit
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by NHS North and East London Commissioning Support Unit and Prescribing Services Ltd.
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 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)
- Medicines Dispensed in Primary Care (NHSBSA Data)
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.
Provide intelligence about the safety and effectiveness of medicines.
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 NHS North and East London Commissioning Support Unit and Optum Health Solutions (UK) Limited.
Optum's analyses of data aims to understand the needs of the population through whole population segmentation. This focuses on the entirety of the Primary Care Networks or Place/Integrated Care Partnership population and differentiates it into segments using a complexity measure and age. Further analyses are presented that stratify individuals in segments according to the presence or risk of poor outcomes. Places/Integrated Care Partnerships and Primary Care Networks have full autonomy to delve into any of the segments to identify cohorts for proactive intervention. Groups of patients of c.100-200 will be identified and pseudonymised NHS numbers passed from Optum to North and East London Commissioning Support Unit support team for reports to be created within North and East London Commissioning Support Unit tooling for GPs with Role Based Access Controls and a legitimate caring relationship with the patients to identify individuals for intervention. Only those who already have a right to access this data e.g. for direct care purposes will be able to view this data.
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify cohorts of patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
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 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. The identification of variation in quality of services and potential efficiencies across pathways
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. In improving the quality of referrals under current structures, CCGs are able to monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. CCGs may 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. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able 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.
23. Allow Commissioners to better protect or improve the public health of the total local patient population.
24. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population.
25. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
26. Linking prescribing habits to entry points into the health and social care system
27. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
Benefits reported
NHS Northamptonshire CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. NHS Northamptonshire CCG will use intelligence to add insight to strategic commissioning and service integration across Northamptonshire. This work will continue year on year to match the delivery/funding of targets services for the population.
DARS-NIC-362252-M1X0V-v1.4 24 August 2020 to 23 August 2023
- Title
- DSfC - NHS Northamptonshire CCG - RS, COMM & IV
- 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 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; SUS for Commissioners
What changed from DARS-NIC-362252-M1X0V-v0.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-08-24 | |
| End date | 2023-08-23 | |
| 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'; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient 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'; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. |
Datasets: + e-Referral Service for Commissioning
Objective for processing
[8 paragraphs unchanged]
Risk Stratification will be conducted by North East London Commissioning Support Unit
and Prescribing Services Ltd.
[31 paragraphs unchanged]
- e-Referral Service (eRS)
[12 paragraphs unchanged]
Patient stratification and predictive modelling - to 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
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.
[1 paragraph unchanged]
Processing for commissioning will be conducted by North East London Commissioning Support
Unit
Unit.
Processing activities
[10 paragraphs unchanged]
The data will flow from NEL DSCRO to NEL CSU data warehouse where it will remain in a secure logically segregated location.
[24 paragraphs unchanged]
Microsoft
UK
Limited
supply provide Cloud Services for North East London Commissioning Support Unit and
[35 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[15 paragraphs unchanged]
3. Identifiable GP Data is securely sent from the GP system to North East London Commissioning Support
Unit.
Unit and Prescribing Services Ltd.
[2 paragraphs unchanged]
6. Once North East London Commissioning Support Unit
has
and Prescribing Services Ltd have
completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
[29 paragraphs unchanged]
16. e-Referral Service (eRS)
[15 paragraphs unchanged]
Expected output
[13 paragraphs unchanged] 5. Identify cohorts of patients at risk of deterioration and providing effective care. [53 paragraphs unchanged] 19. The identification of variation in quality of services and potential efficiencies across pathways 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. In improving the quality of referrals under current structures, CCGs are able to monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 21. CCGs may 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. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able 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.
Expected measurable benefits
[54 paragraphs unchanged] 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 20. Help drive changes in healthcare 21. Allows comparisons of providers performance to assist improvement in services – increase the quality 22. Inform commissioners and improve services 23. 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. 24. Understanding the interdependency of care services 25. Targeting care more effectively 26. Using value as the redesign principle 27. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them 28. 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 29. 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 30. Service redesign 31. Health Needs Assessment – identification of underlying disease prevalence within the local population 32. 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). 33. Support the Age Well agenda through the rapid transformation of services across multiple providers through co-production of targeted interventions across systems and pathways.
Benefits reported
Yielded Benefits is not a requirement for new applications.
NHS Northamptonshire CCG will to build on the yielded benefits of commissioning services that meet the needs of our local population, and that are effective in their delivery. NHS Northamptonshire CCG will use intelligence to add insight to strategic commissioning and service integration across Northamptonshire. This work will continue year on year to match the delivery/funding of targets services for the population.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by North East London Commissioning Support Unit
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by North East London Commissioning Support Unit and Prescribing Services Ltd.
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 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)
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.
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.
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify cohorts of patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
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 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. The identification of variation in quality of services and potential efficiencies across pathways
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. In improving the quality of referrals under current structures, CCGs are able to monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. CCGs may 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. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able 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.
Benefits reported
NHS Northamptonshire CCG will to build on the yielded benefits of commissioning services that meet the needs of our local population, and that are effective in their delivery. NHS Northamptonshire CCG will use intelligence to add insight to strategic commissioning and service integration across Northamptonshire. This work will continue year on year to match the delivery/funding of targets services for the population.
DARS-NIC-362252-M1X0V-v0.2 1 April 2020 to 31 March 2023
- Title
- DSfC - NHS Northamptonshire CCG - RS, COMM & IV
- Commercial
- No
- Sublicensing
- No
- Datasets
- 28
- 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 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; SUS for Commissioners
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by North East London Commissioning Support Unit
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by North East London Commissioning Support Unit
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 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)
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 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 CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North East London Commissioning Support Unit
Expected output
INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
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 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.
Benefits reported
Yielded Benefits is not a requirement for new applications.
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-362252-M1X0V-v0.2, DARS-NIC-362252-M1X0V-v1.4, DARS-NIC-362252-M1X0V-v2.2
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November 2021
1 version added: DARS-NIC-362252-M1X0V-v3.3
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March 2022
1 version added: DARS-NIC-362252-M1X0V-v4.2
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June 2022
1 version added: DARS-NIC-362252-M1X0V-v5.2
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October 2022
Succeeded Applicant organisation: NHS Northamptonshire CCG succeeded by NHS Northamptonshire ICB from 1 July 2022, according to NHS ODS. Not counted as a change.Succeeded Data controllers: NHS Northamptonshire CCG succeeded by NHS Northamptonshire 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-362252-M1X0V-v0.2 — 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-362252-M1X0V, “DSfC - NHS Northamptonshire CCG - RS, COMM & IV”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-362252-m1x0v/ (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-362252-M1X0V to see the original rows.