DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
NHS Surrey Heartlands ICB · Sub ICB Location
Listed under NHS Surrey and Sussex Integrated Care Board.
Expired The latest version ended on 13 March 2025. The September 2026 register still lists the agreement, but its term has passed.
- Reference
- DARS-NIC-362236-D7W4M
- Latest version
- v6.2
- Term of latest version
- 14 March 2022 to 13 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 with be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk 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+) 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 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 The Sollis Partnership, Docobo Ltd and Graphnet Health LTD.
The processing is not excessive or parallel as the platform through which the risk stratification is deployed is different to the pre-existing Sollis Partnership and Docobo solutions due to: -
• The Graphnet risk stratification solution works with near real time updates from primary care providing scores which are based on more up to date data set;
• It provides better decision-making capability for GP's, allowing them to access a wider set of information alongside the stratified data set (e.g. accessing social care, community and mental health pages within the shared cared record);
• The GP's can access the shared care record risk stratification information from within the EMIS clinical solution allowing GP's to access risk stratification information seamlessly.
When the solution is live, the CCG will look to consolidate the use of different solutions and move to a single risk stratification service provider.
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 and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (e-RS)
- 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.
§ 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 areas based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit, Edge Health Limited, Optum Health Solutions Limited, NHS North East London CCG & NHS South West London CCG.
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.
NHS England Wave 2 PHM project
The CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England
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 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 Surrey Heartlands 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 Surrey Heartlands 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 Surrey Heartlands CCG - this is only for commissioning and relates to both national and local flows.
and/or
• Patients treated by a provider where NHS Surrey Heartlands 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 Surrey Heartlands 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 provide Cloud Services for North East London CSU, Graphnet Health Ltd, NHS North of England Commissioning Support Unit , Liaison Financial Services Ltd 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 provide cloud services for Optum Health Solutions (UK) Limited and are therefore listed as 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.
Data Barracks supply IT infrastructure to the CCG 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.
Barking Havering and Redbridge Hospitals NHS Trust, University Hospitals Bristol NHS Foundation Trust, The Bunker Secure Hosting Ltd, 4D Data Centres Ltd, Ark Data Centres, Pulsant, IT Professional Services Ltd and Interxion UK do not access data held under this agreement as they only supply the buildings. 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- Liaison Financial Services Ltd
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 to North East London Commissioning Support Unit who land the data and then push this into the Controlled Environment for Finance (CEfF) in the Liaison Financial Services Ltd.
3. The CEfF also receive backing data from the provider.
4. Liaison Financial Services Ltd 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 Liaison Financial Services Ltd 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.
RISK STRATIFICATION - Graphnet Health Limited
1. Identifiable SUS+ data is obtained 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 Graphnet Health Limited, who securely hold the SUS+ data.
3. Identifiable GP Data is sourced from the CareCentric Surrey Care Record system provided by Graphnet Health Limited.
4. SUS+ data is linked to GP data in the risk stratification algorithm within the CareCentric system by the data processor.
5. GPs will have access to the risk stratification scores within the CareCentric system. Clinicians will open their clinical system and launch CareCentric from within it, to access risk stratification reports.
6. The application allows Clinicians (in this instance GPs) to access risk stratification scores for patients alongside further information from the Surrey Care Record, providing up to date information on events within primary care, secondary care, community care, mental health and social care. This supports better and more effective clinical decision making and saves time for clinicians as they do not have to search through different systems to gather information on a patients care.
7. Once Graphnet Health Limited has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
RISK STRATIFICATION - Sollis Partnership Ltd
1. Identifiable SUS+ data is obtained 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 Sollis Partnership Ltd, who hold the SUS+ data within the secure Data Centre.
3. Identifiable GP Data is securely sent from the GP system to Sollis Partnership 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 Sollis Partnership Ltd has completed the processing, the CCG can access the online system via a secure connection to access the pseudonymised data at patient level.
Risk Stratification - Docobo Ltd
1. Identifiable SUS+ data is obtained 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 Docobo Ltd, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to Docobo 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 Docobo Ltd. has 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)
13. National diabetes Audit (NDA)
14. Patient Reported Outcome Measures (PROMs)
15. e-Referral Service (eRS)
16. Personal Demographics Service (PDS)
17. Summary Hospital-level Mortality Indicator (SHMI)
18. Medicines Dispensed in Primary Care (NHSBSA Data)
19. Adult Social Care Data
Data quality management and pseudonymisation is completed within the DSCRO (using the DSCRO pseudonymisation process) and is then disseminated as follows:
Data Processor 1 – NHS North East London Commissioning Support Unit/NHS North of England 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), Adult Social Care data and e-Referral Service (eRS) only is securely transferred from the DSCRO to NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG.
2. NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG also receive a flow of GP data (see points i - vi)
3. NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
4. Allowed linkage is between the data sets contained within points 1 and 2.
5. NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG then pass the processed, pseudonymised and linked data to the CCG.
6. Aggregation of required data for CCG management use will be completed by NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG or the CCG as instructed by the CCG.
7. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
GP Data
i. Identifiable GP data is submitted to NHS North East London Commissioning Support Unit / North of England Commissioning Support Unit / NHS North East London CCG/NHS South West London CCG.
ii. The identifiable data lands in a ring-fenced area for GP data only.
iii. There is a Data Processing Agreement in place between the GPs and NHS North East London Commissioning Support Unit / North of England Commissioning Support Unit / NHS North East London CCG/NHS South West London CCG. The GP data is pseudonymised using a pseudonymisation key provided by the DSCRO, but different to that used by the DSCRO.
iv. A specific named individual within NHS North East London Commissioning Support Unit / North of England Commissioning Support Unit / NHS North East London CCG/NHS South West London CCG acts on behalf of the GP. This person has access to a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box. This software cannot be interrogated.
v. The individual requests a mapping table from the DSCRO to the black box. The mapping table can only be used once and is specific to that GP and to that specific date. It overwrites the pseudo key to that used by the DSCRO
vi. The CSU / CCGs are then sent the pseudonymised GP data from the ring-fenced area with the pseudo algorithm specific to them.
Data Processor 2 - Optum Health Solutions Ltd
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD), National diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data), Adult Social Care and GP data only is securely transferred from the NHS North East London Commissioning Support Unit / North of England Commissioning Support Unit / NHS North East London CCG/NHS South West London CCG / NHS Surrey Heartlands CCG to Optum Health Solutions (UK) Ltd.
2. Optum Health Solutions (UK) Ltd provide analysis to support the CCGs to:
• See patient journeys for pathways or service design, re-design and de-commissioning
• Undertake population health management
• Undertake data quality and validation checks
• Thoroughly investigate the needs of the population
• Understand cohorts of residents who are at risk
• Conduct Health Needs Assessments
3. Optum Health Solutions (UK) Ltd then pass the processed pseudonymised data to the CCG. Aggregation of required data for CCG management use will be completed by Optum Health Solutions (UK) Ltd or the CCG as instructed by the CCG.
4. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
Data Processor 3 - Edge Health Limited
1. NHS Surrey Heartlands CCG pass pseudonymised patient level data from the following commissioning datasets to Edge Health Limited:
• SUS+
• Local Provider Flows
• Community Services Data Set (CSDS)
• Mental Health Minimum Data Set (MHMDS)
2. Edge Health Limited are permitted to link data from the following datasets only:
• SUS+
• Local Provider Flows
• Community Services Data Set (CSDS)
3. Edge Health Limited provide analysis of the data to support NHS North West Surrey CCG to:
a. See patient journeys for pathways or service design, re-design and de-commissioning
b. Undertake population health management
c. Undertake data quality and validation checks
d. Thoroughly investigate the needs of the population
e. Understand cohorts of residents who are at risk
f. Conduct Health Needs Assessments.
4. Edge Health Limited then pass the processed pseudonymised data to the CCG. Aggregation of required data for CCG management use will be completed by the CCG or Edge Health Limited as instructed by the CCG.
5. Patient level data will not be shared outside of the CCG and authorised processors and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
Expected output
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services will repeat the exercise 2-3 years later
7. CCGs are able to request reviews to be done more frequently
8. SUS+ will only be requested each time a review was completed, and maybe requested at different times as independent reviews
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
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. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment.
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity
32. Suppressed aggregated results that can be shared across the SCW area for bench-marking purposes
33. 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.
34. 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.
35. 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.
36. 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.
37.Allow Commissioners to better protect or improve the public health of the total local patient population
38.Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
39.Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
40.Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
41.Linking prescribing habits to entry points into the health and social care system
42.Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
43. 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
44. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
The outputs, as part of the NHS England Wave 2 PHM Optum national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Financial validation of activity
2. CCG Budget control
3. Assurances over the robustness of internal control mechanisms relating to the payment of invoices and/or suggested improvements
4. Identification and recovery of monies which would otherwise be lost
5. Meeting commissioning objectives without compromising patient confidentiality
6. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
7. Benefit delivered 3-9 months from receiving data, depending on number of claims to investigate and resolve
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
All of the above lead to improved patient experience 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.
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Reviewing current service provision
a. Cost-benefit analysis and service impact assessments to underpin service transformation across health economy
b. Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.)
c. Impact analysis for different models or productivity measures, efficiency and experience
d. Service and pathway review
e. Service utilisation review
15. Ensuring compliance with evidence and guidance
a. Testing approaches with evidence and compliance with guidance.
16. Monitoring outcomes
a. Analysis of variation in outcomes across population group
17. Understanding how services impact across the health economy
a. Service evaluation
b. Programme reviews
c. Analysis of productivity, outcomes, experience, plan, targets and actuals
d. Assessing value for money and efficiency gains
e. Understanding impact of services on health inequalities
18. Understanding how services impact on the health of the population and patient cohorts
a. Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this
b. Propensity matching and scoring
c. Triple aim analysis
19. Understanding future drivers for change across health economy
a. Forecasting health and care needs for population and population cohorts across STPs
b. Identifying changes in disease trends and prevalence
c. Efficiencies that can be gained from procuring services across wider footprints, from new innovations
d. Predictive modelling
20. Delivering services that meet changing needs of population
a. Analysis to support policy development
b. Ethical and equality impact assessments
c. Implementation of NMOC
d. What do next years contracts need to include?
e. Workforce planning
21. Maximising services and outcomes within financial envelopes across health economy
a. What-if analysis
b. Cost-benefit analysis
c. Health economics analysis
d. Scenario planning and modelling
e. Investment and disinvestment in services analysis
f. Opportunity analysis
22. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
23. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
24. Provision of indicators of health problems, and patterns of risk within the commissioning region.
25. Support of benchmarking for evaluating progress in future years.
26. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
27. Assists commissioners to make better decisions to support patients and drive changes in health care
28. Allows comparisons of providers performance to assist improvement in services – increase the quality
29. 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.
30. 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).
31. Monitoring of entire population, as a pose to only those that engage with services
32. 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.
33. Monitor the quality and safety of the delivery of healthcare services.
34. Allow focused commissioning support based on factual data rather than assumed and projected sources.
35. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
36.Understand admissions linked to overprescribing.
37. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
38. Designing and implementing new payment models across health and adult social care
39. 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
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience. The CCG has also produced an annual report which details the key development and achievements for which processing NHS Digital data has been used to support. The report can be found at:
https://www.surreyheartlandsccg.nhs.uk/about-us/our-publications/annual-report
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-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 7 versions.
DARS-NIC-362236-D7W4M-v6.2 14 March 2022 to 13 March 2025
- Title
- DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
- Commercial
- No
- Sublicensing
- No
- Datasets
- 32
- 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-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-362236-D7W4M-v5.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2022-03-14 | |
| End date | 2025-03-13 |
Objective for processing
[9 paragraphs unchanged]
Risk Stratification will be conducted by The Sollis Partnership, Docobo Ltd and Graphnet
healthcare
Health
LTD.
[59 paragraphs unchanged]
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit, Edge Health
Limited and
Limited,
Optum Health Solutions
Limited.
Limited, NHS North East London CCG & NHS South West London CCG.
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.
[2 paragraphs unchanged]
Processing activities
[9 paragraphs unchanged]
The
only
identifier available in the data set is the NHS numbers. Any further
[14 words unchanged]
own systems for the purpose of direct care with a legitimate relationship.
[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 NHS Surrey Heartlands 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 provide Cloud Services for North East London CSU, Graphnet Health Ltd,
NHS North of England Commissioning Support Unit ,
Liaison Financial Services
Ltd, North of England CSU,
Ltd
and Optum Health Solutions (UK) Limited and are therefore listed as a
[30 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[2 paragraphs unchanged]
Barking Havering and Redbridge Hospitals NHS Trust,
University Hospitals Bristol NHS Foundation Trust, The Bunker Secure Hosting Ltd, 4D Data Centres Ltd, Ark Data
Centres
Centres, Pulsant, IT Professional Services Ltd
and Interxion UK do not access data held under this agreement as
[22 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[78 paragraphs unchanged]
Data Processor 1 – NHS North East London Commissioning Support Unit/NHS North of England 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),
[82 words unchanged]
NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support
Unit.
Unit/NHS North East London CCG/NHS South West London CCG.
2. NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support
Unit add derived fields, link
Unit/NHS North East London CCG/NHS South West London CCG also receive a flow of GP
data
and provide analysis to:
(see points i - vi)
3. NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit/NHS North East London CCG/NHS South West London CCG add derived fields, link data and provide analysis to:
[7 paragraphs unchanged]
3.
4.
Allowed linkage is between the data sets contained within
point 1.
points 1 and 2.
4.
5.
NHS North East London Commissioning Support Unit/NHS North of England 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.
5.
6.
Aggregation of required data for CCG management use will be completed by NHS North East London Commissioning Support Unit/NHS North of England Commissioning Support
Unit
Unit/NHS North East London CCG/NHS South West London CCG
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.
GP Data
i. Identifiable GP data is submitted to NHS North East London Commissioning Support Unit / North of England Commissioning Support Unit / NHS North East London CCG/NHS South West London CCG.
ii. The identifiable data lands in a ring-fenced area for GP data only.
iii. There is a Data Processing Agreement in place between the GPs and NHS North East London Commissioning Support Unit / North of England Commissioning Support Unit / NHS North East London CCG/NHS South West London CCG. The GP data is pseudonymised using a pseudonymisation key provided by the DSCRO, but different to that used by the DSCRO.
iv. A specific named individual within NHS North East London Commissioning Support Unit / North of England Commissioning Support Unit / NHS North East London CCG/NHS South West London CCG acts on behalf of the GP. This person has access to a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box. This software cannot be interrogated.
v. The individual requests a mapping table from the DSCRO to the black box. The mapping table can only be used once and is specific to that GP and to that specific date. It overwrites the pseudo key to that used by the DSCRO
vi. The CSU / CCGs are then sent the pseudonymised GP data from the ring-fenced area with the pseudo algorithm specific to them.
[1 paragraph unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[58 words unchanged]
Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data), Adult Social Care
and GP
data only is securely transferred from the
DSCRO to
NHS
North East London Commissioning Support
Unit/NHS
Unit /
North of England Commissioning Support
Unit.
Unit / NHS North East London CCG/NHS South West London CCG / NHS Surrey Heartlands CCG to Optum Health Solutions (UK) Ltd.
2. North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit also receive identifiable GP data for a GP Practices within the CCGs area. The GP data is received and process as per points i-iv below.
2. Optum Health Solutions (UK) Ltd provide analysis to support the CCGs to:
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/NECS 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/NECS 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.
iv. The agreed specification of Pseudonymised GP data is then made available to CCGs via a secure means of transfer from the secure NEL CSU/NECS GP environment to the destination CCG or CSU environment where only pseudonymised data resides.
3. a) North East London Commissioning Support Unit/NHS North of England Commissioning Support Unit securely transfer the pseudonymised data in point 1 and point 2 to NHS Surrey Heartlands CCG.
b) NHS Surrey Heartlands CCG are permitted to link pseudonymised data listed in point 1 and point 2.
c) NHS Surrey Heartlands CCG then pass the pseudonymised data to Optum Health Solutions (UK) Ltd.
4. Optum Health Solutions (UK) Ltd provide analysis to support the CCGs to:
[6 paragraphs unchanged]
5.
3.
Optum Health Solutions (UK) Ltd then pass the processed pseudonymised data to
[15 words unchanged]
Health Solutions (UK) Ltd or the CCG as instructed by the CCG.
6.
4.
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.
[19 paragraphs unchanged]
Benefits reported
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience. The CCG has also produced an annual report which details the key development and achievements for which processing NHS Digital data has been used to support. The report can be found at:
Listed below is a number of further yielded benefits for commissioning;
https://www.surreyheartlandsccg.nhs.uk/about-us/our-publications/annual-report
1. Monitoring In year projects
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
3. Successful delivery of integrated care within the CCG.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
The 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. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
Unchanged: Expected output, Expected measurable benefits.
DARS-NIC-362236-D7W4M-v5.2 23 November 2021 to 22 November 2024
- Title
- DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
- Commercial
- No
- Sublicensing
- No
- Datasets
- 32
- 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-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-362236-D7W4M-v4.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2021-11-23 | |
| End date | 2024-11-22 | |
| Ambulance-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' |
Unchanged: Objective for processing, Processing activities, Expected output, Expected measurable benefits, 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 with be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk 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+) 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 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 The Sollis Partnership, Docobo Ltd and Graphnet healthcare LTD.
The processing is not excessive or parallel as the platform through which the risk stratification is deployed is different to the pre-existing Sollis Partnership and Docobo solutions due to: -
• The Graphnet risk stratification solution works with near real time updates from primary care providing scores which are based on more up to date data set;
• It provides better decision-making capability for GP's, allowing them to access a wider set of information alongside the stratified data set (e.g. accessing social care, community and mental health pages within the shared cared record);
• The GP's can access the shared care record risk stratification information from within the EMIS clinical solution allowing GP's to access risk stratification information seamlessly.
When the solution is live, the CCG will look to consolidate the use of different solutions and move to a single risk stratification service provider.
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 and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (e-RS)
- 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.
§ 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 areas based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit, Edge Health Limited and Optum Health Solutions Limited.
NHS England Wave 2 PHM project
The CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services will repeat the exercise 2-3 years later
7. CCGs are able to request reviews to be done more frequently
8. SUS+ will only be requested each time a review was completed, and maybe requested at different times as independent reviews
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
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. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment.
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity
32. Suppressed aggregated results that can be shared across the SCW area for bench-marking purposes
33. 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.
34. 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.
35. 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.
36. 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.
37.Allow Commissioners to better protect or improve the public health of the total local patient population
38.Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
39.Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
40.Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
41.Linking prescribing habits to entry points into the health and social care system
42.Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
43. 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
44. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
The outputs, as part of the NHS England Wave 2 PHM Optum national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population
Benefits reported
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
Listed below is a number of further yielded benefits for commissioning;
1. Monitoring In year projects
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
3. Successful delivery of integrated care within the CCG.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
The 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. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
DARS-NIC-362236-D7W4M-v4.3 4 August 2021 to 3 August 2024
- Title
- DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
- Commercial
- No
- Sublicensing
- No
- Datasets
- 32
- 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-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-362236-D7W4M-v3.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Ambulance-Local Provider Flows: legal basis | Not stated |
Datasets: + Adult Social Care
Objective for processing
[4 paragraphs unchanged] Invoice Validation with be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Liaison Financial Services Ltd. [64 paragraphs unchanged] Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit, Edge Health Limited and Optum Health Solutions Limited. [2 paragraphs unchanged]
Processing activities
[46 paragraphs unchanged]
Microsoft Limited provide Cloud Services for North East London CSU, Graphnet Health Ltd, Liaison Financial Services
Ltd
Ltd, North of England CSU,
and Optum Health Solutions (UK) Limited and are therefore listed as a
[30 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[3 paragraphs unchanged]
INVOICE VALIDATION - 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.
[1 paragraph 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.
[67 paragraphs unchanged]
Data Processor 1 – NHS North East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[76 words unchanged]
securely transferred from the DSCRO to NHS North East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit.
2. NHS North East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit add derived fields, link data and provide analysis to:
[8 paragraphs unchanged]
4. NHS North 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 NHS North East London Commissioning Support
Unit/NHS North of England Commissioning Support
Unit or the CCG as instructed by the CCG.
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[72 words unchanged]
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 identifiable GP data for a GP Practices within the CCGs area. The GP data is received and process as per points i-iv below.
[1 paragraph unchanged]
ii. Extracted data lands on secure NEL
CSU
CSU/NECS
GP Environment where strict access is limited to individuals who have been
[9 words unchanged]
Risk Owner and act on behalf of the Data Controller (GP Practice).
iii. The NEL
CSU
CSU/NECS
Pseudonym is then applied to GP data within Secure GP Data Environment
[6 words unchanged]
pseudonymisation enables the linkage with other data sets specified in this DSA.
iv. The agreed specification of Pseudonymised GP data is then made available to CCGs via a secure means of transfer from the secure NEL
CSU
CSU/NECS
GP environment to the destination CCG or CSU environment where only pseudonymised data resides.
3. a) North East London
Commissioning Support Unit/NHS North of England
Commissioning Support Unit securely transfer the pseudonymised data in point 1 and point 2 to NHS Surrey Heartlands CCG.
[30 paragraphs unchanged]
Unchanged: Expected output, Expected measurable benefits, 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 with be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk 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+) 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 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 The Sollis Partnership, Docobo Ltd and Graphnet healthcare LTD.
The processing is not excessive or parallel as the platform through which the risk stratification is deployed is different to the pre-existing Sollis Partnership and Docobo solutions due to: -
• The Graphnet risk stratification solution works with near real time updates from primary care providing scores which are based on more up to date data set;
• It provides better decision-making capability for GP's, allowing them to access a wider set of information alongside the stratified data set (e.g. accessing social care, community and mental health pages within the shared cared record);
• The GP's can access the shared care record risk stratification information from within the EMIS clinical solution allowing GP's to access risk stratification information seamlessly.
When the solution is live, the CCG will look to consolidate the use of different solutions and move to a single risk stratification service provider.
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 and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (e-RS)
- 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.
§ 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 areas based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, NHS North of England Commissioning Support Unit, Edge Health Limited and Optum Health Solutions Limited.
NHS England Wave 2 PHM project
The CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services will repeat the exercise 2-3 years later
7. CCGs are able to request reviews to be done more frequently
8. SUS+ will only be requested each time a review was completed, and maybe requested at different times as independent reviews
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
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. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment.
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity
32. Suppressed aggregated results that can be shared across the SCW area for bench-marking purposes
33. 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.
34. 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.
35. 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.
36. 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.
37.Allow Commissioners to better protect or improve the public health of the total local patient population
38.Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
39.Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
40.Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
41.Linking prescribing habits to entry points into the health and social care system
42.Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
43. 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
44. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
The outputs, as part of the NHS England Wave 2 PHM Optum national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population
Benefits reported
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
Listed below is a number of further yielded benefits for commissioning;
1. Monitoring In year projects
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
3. Successful delivery of integrated care within the CCG.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
The 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. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
DARS-NIC-362236-D7W4M-v3.2 4 August 2021 to 3 August 2024
- Title
- DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
- Commercial
- No
- Sublicensing
- No
- Datasets
- 31
- 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-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-362236-D7W4M-v2.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2021-08-04 | |
| End date | 2024-08-03 |
Datasets: + Medicines dispensed in Primary Care (NHSBSA data)
Objective for processing
[9 paragraphs unchanged]
Risk Stratification will be conducted by The Sollis
Partnership and
Partnership,
Docobo Ltd
and Graphnet healthcare LTD.
The processing is not excessive or parallel as the platform through which the risk stratification is deployed is different to the pre-existing Sollis Partnership and Docobo solutions due to: -
• The Graphnet risk stratification solution works with near real time updates from primary care providing scores which are based on more up to date data set;
• It provides better decision-making capability for GP's, allowing them to access a wider set of information alongside the stratified data set (e.g. accessing social care, community and mental health pages within the shared cared record);
• The GP's can access the shared care record risk stratification information from within the EMIS clinical solution allowing GP's to access risk stratification information seamlessly.
When the solution is live, the CCG will look to consolidate the use of different solutions and move to a single risk stratification service provider.
[33 paragraphs unchanged]
-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.
[4 paragraphs unchanged]
· Using value as the redesign principle
[9 paragraphs unchanged]
§ Support measuring the health, mortality or care needs of the total local
population
population.
§ 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
[4 paragraphs unchanged]
Processing activities
[11 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 provide Cloud Services for North East London CSU,
Graphnet Health Ltd,
Liaison Financial Services Ltd and Optum Health Solutions (UK) Limited and are
[34 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[25 paragraphs unchanged]
RISK STRATIFICATION - Graphnet Health Limited
1. Identifiable SUS+ data is obtained 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 Graphnet Health Limited, who securely hold the SUS+ data.
3. Identifiable GP Data is sourced from the CareCentric Surrey Care Record system provided by Graphnet Health Limited.
4. SUS+ data is linked to GP data in the risk stratification algorithm within the CareCentric system by the data processor.
5. GPs will have access to the risk stratification scores within the CareCentric system. Clinicians will open their clinical system and launch CareCentric from within it, to access risk stratification reports.
6. The application allows Clinicians (in this instance GPs) to access risk stratification scores for patients alongside further information from the Surrey Care Record, providing up to date information on events within primary care, secondary care, community care, mental health and social care. This supports better and more effective clinical decision making and saves time for clinicians as they do not have to search through different systems to gather information on a patients care.
7. Once Graphnet Health Limited has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
[43 paragraphs unchanged]
16.Personal
16. Personal
Demographics Service (PDS)
17.Summary
17. Summary
Hospital-level Mortality Indicator (SHMI)
18. Medicines Dispensed in Primary Care (NHSBSA Data)
19. Adult Social Care Data
[2 paragraphs unchanged]
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)
(SHMI), Medicines Dispensed in Primary Care (NHSBSA Data), Adult Social Care
data and e-Referral Service (eRS) only is securely transferred from the DSCRO to NHS North East London Commissioning Support Unit.
[13 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[47 words unchanged]
e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator
(SHMI)
(SHMI), Medicines Dispensed in Primary Care (NHSBSA Data), Adult Social Care
data only is securely transferred from the DSCRO to North East London Commissioning Support Unit.
[36 paragraphs unchanged]
Expected output
[152 paragraphs unchanged]
40.Investigate mortality outcomes for
trusts
trusts.
Identify medication prescribing trends and their effectiveness.
41.Linking prescribing habits to entry points into the health and social care system
42.Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
43. 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
44. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
[2 paragraphs unchanged]
Expected measurable benefits
[108 paragraphs unchanged]
34. Allow focused commissioning support based on factual data rather than assumed and projected
sources
sources.
35. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
36.Understand admissions linked to overprescribing.
37. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
38. Designing and implementing new payment models across health and adult social care
39. 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
Not stated in the previous version; added here.
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
Listed below is a number of further yielded benefits for commissioning;
1. Monitoring In year projects
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
3. Successful delivery of integrated care within the CCG.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
The 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. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
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 with be conducted by NHS North East London Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk 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+) 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 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 The Sollis Partnership, Docobo Ltd and Graphnet healthcare LTD.
The processing is not excessive or parallel as the platform through which the risk stratification is deployed is different to the pre-existing Sollis Partnership and Docobo solutions due to: -
• The Graphnet risk stratification solution works with near real time updates from primary care providing scores which are based on more up to date data set;
• It provides better decision-making capability for GP's, allowing them to access a wider set of information alongside the stratified data set (e.g. accessing social care, community and mental health pages within the shared cared record);
• The GP's can access the shared care record risk stratification information from within the EMIS clinical solution allowing GP's to access risk stratification information seamlessly.
When the solution is live, the CCG will look to consolidate the use of different solutions and move to a single risk stratification service provider.
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 and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (e-RS)
- 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.
§ 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 areas based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, Edge Health Limited and Optum Health Solutions Limited.
NHS England Wave 2 PHM project
The CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services will repeat the exercise 2-3 years later
7. CCGs are able to request reviews to be done more frequently
8. SUS+ will only be requested each time a review was completed, and maybe requested at different times as independent reviews
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
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. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment.
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity
32. Suppressed aggregated results that can be shared across the SCW area for bench-marking purposes
33. 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.
34. 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.
35. 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.
36. 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.
37.Allow Commissioners to better protect or improve the public health of the total local patient population
38.Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
39.Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
40.Investigate mortality outcomes for trusts.
Identify medication prescribing trends and their effectiveness.
41.Linking prescribing habits to entry points into the health and social care system
42.Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy).
43. 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
44. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
The outputs, as part of the NHS England Wave 2 PHM Optum national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population
Benefits reported
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
Listed below is a number of further yielded benefits for commissioning;
1. Monitoring In year projects
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
3. Successful delivery of integrated care within the CCG.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
The 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. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
DARS-NIC-362236-D7W4M-v2.2 5 December 2020 to 6 December 2023
- Title
- DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
- Commercial
- No
- Sublicensing
- No
- Datasets
- 30
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Personal Demographic Service; Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; Summary Hospital-level Mortality Indicator (SHMI); SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-362236-D7W4M-v1.4
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-12-05 | |
| End date | 2023-12-06 | |
| Acute-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Ambulance-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Children and Young People Health: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registration - Births: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registrations of Death: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community Services Data Set (CSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Demand for Service-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Imaging Data Set (DID): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Emergency Care-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Experience, Quality and Outcomes-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Improving Access to Psychological Therapies Data Set_v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Maternity Services Data Set v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Minimum Data Set (MHMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Services Data Set (MHSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health and Learning Disabilities Data Set (MHLDDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Diabetes Audit: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Patient Reported Outcome Measures (PROMs): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Population Data-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Primary Care Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Public Health and Screening Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| SUS for Commissioners: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. | |
| e-Referral Service for Commissioning: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' |
Datasets: + Personal Demographic Service; + Summary Hospital-level Mortality Indicator (SHMI)
Objective for processing
[4 paragraphs unchanged]
Invoice Validation with be conducted by NHS North East London Commissioning Support Unit and Liaison Financial
Services.
Services Ltd.
[36 paragraphs unchanged]
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
[13 paragraphs unchanged]
§ 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
[4 paragraphs unchanged]
Processing activities
[34 paragraphs unchanged]
Microsoft Limited
supply
provide Cloud Services
for North East London CSU, Liaison Financial Services Ltd 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.
Amazon Web Services provide cloud services for Optum Health Solutions (UK) Limited and are therefore listed as 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.
[13 paragraphs unchanged]
INVOICE VALIDATION - South Central and West 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 South Central and West Commissioning Support Unit.
3. The CEfF also receive backing data from the provider.
4. South Central and West 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 South Central and West 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.
[17 paragraphs unchanged]
6. Once Sollis Partnership Ltd has completed the processing, the CCG can access the online system via a secure connection to access the
pseudonymised
data
aggregate with small number suppression.
at patient level.
[36 paragraphs unchanged]
16.Personal Demographics Service (PDS)
17.Summary Hospital-level Mortality Indicator (SHMI)
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[37 words unchanged]
(CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures
(PROMs)
(PROMs), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI) data
and e-Referral Service (eRS) only is securely transferred from the DSCRO to NHS North East London Commissioning Support Unit.
[13 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[34 words unchanged]
Civil Registries Data (CRD), National diabetes Audit (NDA), Patient Reported Outcome Measures
(PROMs) and
(PROMs),
e-Referral Service
(eRS)
(eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI) data
only is securely transferred from the DSCRO to North East London Commissioning Support Unit.
[36 paragraphs unchanged]
Expected output
[149 paragraphs unchanged] 37.Allow Commissioners to better protect or improve the public health of the total local patient population 38.Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population 39.Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 40.Investigate mortality outcomes for trusts [2 paragraphs unchanged]
Expected measurable benefits
[101 paragraphs unchanged]
27. Assists commissioners to make better decisions to support patients
and drive changes in health care
28. Help drive changes in healthcare
28. Allows comparisons of providers performance to assist improvement in services – increase the quality
29. Allows comparisons of providers performance to assist improvement in services – increase the quality
29. 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.
30. Inform commissioners and improve services
30. 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).
31. 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.
31. Monitoring of entire population, as a pose to only those that engage with services
32. Understanding the interdependency of care services
32. 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.
33. Targeting care more effectively
33. Monitor the quality and safety of the delivery of healthcare services.
34. Using value as the redesign principle
34. Allow focused commissioning support based on factual data rather than assumed and projected sources
35. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
36. 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
37. 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
38. Service redesign
39. Health Needs Assessment – identification of underlying disease prevalence within the local population
40. 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).
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 with be conducted by NHS North East London Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk 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+) 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 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 The Sollis Partnership and Docobo 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 and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (e-RS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
The pseudonymised data is required to for the following purposes:
§ Population health management:
· Understanding the interdependency of care services
· Targeting care more effectively
· Using value as the redesign principle
§ Data Quality and Validation – allowing data quality checks on the submitted data
§ Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§ Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§ Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
§ Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
§ Support measuring the health, mortality or care needs of the total local population
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG areas based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, Edge Health Limited and Optum Health Solutions Limited.
NHS England Wave 2 PHM project
The CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services will repeat the exercise 2-3 years later
7. CCGs are able to request reviews to be done more frequently
8. SUS+ will only be requested each time a review was completed, and maybe requested at different times as independent reviews
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
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. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment.
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity
32. Suppressed aggregated results that can be shared across the SCW area for bench-marking purposes
33. 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.
34. 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.
35. 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.
36. 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.
37.Allow Commissioners to better protect or improve the public health of the total local patient population
38.Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
39.Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
40.Investigate mortality outcomes for trusts
The outputs, as part of the NHS England Wave 2 PHM Optum national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population
DARS-NIC-362236-D7W4M-v1.4 18 May 2020 to 17 May 2023
- Title
- DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
- 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; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); 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-362236-D7W4M-v0.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-05-18 | |
| End date | 2023-05-17 |
Datasets: + e-Referral Service for Commissioning
Objective for processing
[4 paragraphs unchanged]
Invoice Validation with be conducted by
NHS South, Central and West Commissioning Support Unit,
NHS North East London Commissioning Support Unit and Liaison Financial Services.
NHS South, Central and West Commissioning Support Unit and NHS North East London Commissioning Support Unit will process during a dual running period while processing for this is changed from NHS South, Central and West Commissioning Support Unit to NHS North East London Commissioning Support Unit
[35 paragraphs unchanged]
- e-Referral Service (e-RS)
[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
[1 paragraph unchanged]
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit,
NHS South, Central and West Commissioning Support Unit
Edge Health Limited
and Optum Health Solutions Limited.
NHS South Central and West Commissioning Support Unit's commissioning processing is required in addition to the processing of NHS North East London Commissioning Support Unit. This is because the CCG shares suppressed aggregated results with other CCG's in the SCW area. In order to make these results comparable, the processing is needed to be carried out by the same processor.
[2 paragraphs unchanged]
Processing activities
[34 paragraphs unchanged]
Microsoft
UK
Limited
supply provide Cloud Services and are therefore listed as a data processor.
[28 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[2 paragraphs unchanged]
INVOICE VALIDATION - North East London 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.
3. The CEfF also receive backing data from the provider.
4. North East London 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 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.
[64 paragraphs unchanged]
15. e-Referral Service (eRS)
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[32 words unchanged]
Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit
(NDA) and
(NDA),
Patient Reported Outcome Measures (PROMs)
and e-Referral Service (eRS)
only is securely transferred from the DSCRO to NHS North East London Commissioning Support Unit.
[12 paragraphs unchanged]
Data Processor 2 – NHS South Central and West Commissioning Support Unit
Data Processor 2 - Optum Health Solutions Ltd
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[25 words unchanged]
(DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data
(CRD) (Births and Deaths),
(CRD),
National
Diabetes
diabetes
Audit
(NDA) and
(NDA),
Patient Reported Outcome Measures (PROMs)
and e-Referral Service (eRS)
only is securely transferred from the DSCRO to
NHS South Central and West
North East London
Commissioning Support
Unit
Unit.
2. NHS South Central and West Commissioning Support Unit add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. NHS South Central and West 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 NHS South Central and West Commissioning Support Unit or the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
Data Processor 3 - Optum Health Solutions Ltd
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD), National diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs) only is securely transferred from the DSCRO to North East London Commissioning Support Unit.
[17 paragraphs unchanged]
Data Processor 3 - Edge Health Limited
1. NHS Surrey Heartlands CCG pass pseudonymised patient level data from the following commissioning datasets to Edge Health Limited:
• SUS+
• Local Provider Flows
• Community Services Data Set (CSDS)
• Mental Health Minimum Data Set (MHMDS)
2. Edge Health Limited are permitted to link data from the following datasets only:
• SUS+
• Local Provider Flows
• Community Services Data Set (CSDS)
3. Edge Health Limited provide analysis of the data to support NHS North West Surrey CCG to:
a. See patient journeys for pathways or service design, re-design and de-commissioning
b. Undertake population health management
c. Undertake data quality and validation checks
d. Thoroughly investigate the needs of the population
e. Understand cohorts of residents who are at risk
f. Conduct Health Needs Assessments.
4. Edge Health Limited then pass the processed pseudonymised data to the CCG. Aggregation of required data for CCG management use will be completed by the CCG or Edge Health Limited as instructed by the CCG.
5. Patient level data will not be shared outside of the CCG and authorised processors and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
Expected output
[22 paragraphs unchanged] 5. Identify cohorts of patients at risk of deterioration and providing effective care. [122 paragraphs unchanged] 33. 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. 34. 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. 35. 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. 36. 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. [2 paragraphs unchanged]
Expected measurable benefits
[100 paragraphs unchanged] 26. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 27. Assists commissioners to make better decisions to support patients 28. Help drive changes in healthcare 29. Allows comparisons of providers performance to assist improvement in services – increase the quality 30. Inform commissioners and improve services 31. 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. 32. Understanding the interdependency of care services 33. Targeting care more effectively 34. Using value as the redesign principle 35. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them 36. 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 37. 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 38. Service redesign 39. Health Needs Assessment – identification of underlying disease prevalence within the local population 40. 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).
Benefits reported
Stated in the previous version and removed here.
Yielded Benefits is not a requirement for new applications.
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 with be conducted by NHS North East London Commissioning Support Unit and Liaison Financial Services.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk 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+) 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 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 The Sollis Partnership and Docobo 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 and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (e-RS)
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
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 areas based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, Edge Health Limited and Optum Health Solutions Limited.
NHS England Wave 2 PHM project
The CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services will repeat the exercise 2-3 years later
7. CCGs are able to request reviews to be done more frequently
8. SUS+ will only be requested each time a review was completed, and maybe requested at different times as independent reviews
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
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. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment.
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity
32. Suppressed aggregated results that can be shared across the SCW area for bench-marking purposes
33. 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.
34. 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.
35. 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.
36. 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.
The outputs, as part of the NHS England Wave 2 PHM Optum national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population
DARS-NIC-362236-D7W4M-v0.2 1 April 2020 to 31 March 2023
- Title
- DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning
- Commercial
- No
- Sublicensing
- No
- Datasets
- 27
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; SUS for Commissioners; 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 with be conducted by NHS South, Central and West Commissioning Support Unit, NHS North East London Commissioning Support Unit and Liaison Financial Services.
NHS South, Central and West Commissioning Support Unit and NHS North East London Commissioning Support Unit will process during a dual running period while processing for this is changed from NHS South, Central and West Commissioning Support Unit to NHS North East London Commissioning Support Unit
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk 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+) 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 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 The Sollis Partnership and Docobo 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 and Deaths)
- National diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
§ Population health management:
· Understanding the interdependency of care services
· Targeting care more effectively
· Using value as the redesign principle
§ Data Quality and Validation – allowing data quality checks on the submitted data
§ Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§ Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§ Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to 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 areas based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by NHS North East London Commissioning Support Unit, NHS South, Central and West Commissioning Support Unit and Optum Health Solutions Limited.
NHS South Central and West Commissioning Support Unit's commissioning processing is required in addition to the processing of NHS North East London Commissioning Support Unit. This is because the CCG shares suppressed aggregated results with other CCG's in the SCW area. In order to make these results comparable, the processing is needed to be carried out by the same processor.
NHS England Wave 2 PHM project
The CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England
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.
INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services will repeat the exercise 2-3 years later
7. CCGs are able to request reviews to be done more frequently
8. SUS+ will only be requested each time a review was completed, and maybe requested at different times as independent reviews
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
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. Identifying and managing preventable and existing conditions
a. Identifying types of individuals and population cohorts at risk of non-elective re-admission
b. Risk stratification to identify populations suitable for case management
c. Risk profiling and predictive modelling
d. Risk stratification for planning services for population cohorts
e. Identification of disease incidence and diagnosis stratification
14. Reducing health inequalities
a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs
b. Socio-demographic analysis
15. Managing demand
a. Waiting times analysis
b. Service demand and supply modelling
c. Understanding cross-border and overseas visitor
d. Winter planning
e. Emergency preparedness, business continuity, recovery and contingency planning
16. Care co-ordination and planning
a. Planning packages of care
b. Service planning
c. Planning care co-ordination
17. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
a. Patient pathway analysis across health and care
b. Outcomes & experience analysis
c. Analysis to support anti-terror initiatives
d. Analysis to identify vulnerable patients with potential safeguarding issues
e. Understanding equity of care and unwarranted variation
f. Modelling patient flow
g. Tracking patient pathways
h. Monitoring to support New Models of Care
i. Identifying duplications in care
j. Identifying gaps in care, missed diagnoses and triple fail events
k. Analysing individual and aggregated timelines
18. Undertaking budget planning, management and reporting
a. Tracking financial performance against plans
b. Budget reporting
c. Tariff development
d. Developing and monitoring capitated budgets
e. Developing and monitoring individual-level budgets
f. Future budget planning and forecasting
g. Paying for care of overseas visitors and cross-border flow
19. Monitoring the value for money
a. Service-level costing & comparisons
b. Identification of cost pressures
c. Cost benefit analysis
d. Equity of spend across services and population cohorts
e. Finance impact assessment
20. Comparing population groups, peers, national and international best practice
a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
b. Benchmarking against other parts of the country
c. Identifying unwarranted variations
21. Comparing expected levels
a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
22. Comparing local targets & plan
a. Monitoring of local variation in productivity, cost, outcomes, quality and experience
b. Local performance dashboards by service provider, commissioner, geography, NMOC
23. Monitoring activity and cost compliance against contract and agreed plans
a. Contract monitoring
b. Contract reconciliation and challenge
c. Invoice validation
24. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
a. Performance dashboards
b. CQUIN reporting
c. Clinical audit
d. Patient experience surveys
e. Demand, supply, outcome & experience analysis
f. Monitoring cross-border flows and overseas visitor activity
25. Improving provider data quality
a. Coding audit
b. Data quality validation and review
c. Checking validity of patient identity and commissioner assignment.
26. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
27. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
28. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
29. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
30. Removal of patients from Risk Stratification reports.
31. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity
32. Suppressed aggregated results that can be shared across the SCW area for bench-marking purposes
The outputs, as part of the NHS England Wave 2 PHM Optum national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population
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.
-
July 2021 —
already listed in the earliest edition this site holds, so it may be older. 3 versions: DARS-NIC-362236-D7W4M-v0.2, DARS-NIC-362236-D7W4M-v1.4, DARS-NIC-362236-D7W4M-v2.2
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October 2021
1 version added: DARS-NIC-362236-D7W4M-v3.2
-
November 2021
1 version added: DARS-NIC-362236-D7W4M-v4.3
-
January 2022
1 version added: DARS-NIC-362236-D7W4M-v5.2
-
April 2022
1 version added: DARS-NIC-362236-D7W4M-v6.2
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October 2022
Succeeded Applicant organisation: NHS Surrey Heartlands CCG succeeded by NHS Surrey Heartlands ICB from 1 July 2022, according to NHS ODS. Not counted as a change.Succeeded Data controllers: NHS Surrey Heartlands CCG succeeded by NHS Surrey Heartlands 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-362236-D7W4M-v0.2, DARS-NIC-362236-D7W4M-v1.4 — 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-362236-D7W4M, “DSfC - NHS Surrey Heartlands CCG - RS, IV, Commissioning”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-362236-d7w4m/ (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-362236-D7W4M to see the original rows.