DSfC - NHS Kent and Medway CCG - IV, RS & Comm
NHS Kent and Medway ICB · Sub ICB Location
Listed under NHS Kent and Medway Integrated Care Board.
Expired The latest version ended on 19 April 2025. The September 2026 register still lists the agreement, but its term has passed.
- Reference
- DARS-NIC-362255-K5D1H
- Latest version
- v4.3
- Term of latest version
- 20 April 2022 to 19 April 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 able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+), 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).
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by Liaison Financial Services Ltd & NHS Kent and Medway CCG.
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 (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Ltd.
COMMISSIONING
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
- Adult Social Care
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
Provide intelligence about the safety and effectiveness of medicines.
Risk Stratification using pseudo data – using a tool for identifying pseudonymised patients at risk. The pseudonymised patient level data is then shared with health and care professionals with a legitimate relationship to the patient who are able to request re-identification when required for direct care purposes.
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population.
Provide intelligence about the safety and effectiveness of medicines.
Allow analysis of patient pathways across healthcare and social care.
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by MedeAnalytics International Limited, NHS South Central and West Commissioning Support Unit, Maidstone and Tunbridge Wells NHS Trust and Outcomes Based Health Care Limited & NHS Kent and Medway CCG.
Outcomes Based Healthcare Limited will use pseudonymised data, to support population segmentation and measurement of outcomes, for population health management. This includes development of a segmentation model, outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of the CCG. This will enable near real-time outcome measurement for specific population segments, where the entire GP registered population is accounted for.
Health Informatics Service Business Intelligence (HISbi), a semi-autonomous department hosted by Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data including loading and structuring of the data, as well as data quality checks
Processing activities
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.
Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.
ONWARD SHARING:
In the development of cohorts of pseudonymised patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct health or care professionals for the purpose of direct care. Additionally clinicians, made aware of a number of cases that they believe would need intervention may request re-identification for that direct care purpose. These instances of re-identification will generally be carried out as programmes of work or, rarely, on an individual/small group basis.
NHS Digital provides a re-identification service for this process. All re-id requests will be processed and authorised by NHS Digital on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.
The following are typical examples of instances where a CCG might want to use the re-identification process:
A&E High Attendance usage
The CCG can filter data to show for example the number of A&E attendances in a given period for each patient. The CCG can then flag to the relevant GP of the patient any patients that require intervention. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk.
Polypharmacy re-IDs
CCGs can request re-ID of a list of patients to be sent to the relevant GP with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.
The Re-identification process for direct care is as follows:
1. The CCG identifies a patient cohort to be re-identified for the purpose of direct care.
2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSU’s Business Intelligence (BI) Tool, or through a manual form.
3. The DSCRO assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system.
4. For automated systems, steps 1 - 3 wouldn’t apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without further checks.
5. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or Care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
6. DSCROs retain an audit trail of all re-id requests
The Re-identification process for direct care via MedeAnalytics is as follows:
GP Practice staff are able to access de-identified data for patients registered to their own practice.
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
Only GP Practice users are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify have access to encrypted data, and can only access data to which they have rights under RBAC
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.
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 Kent and Medway 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 Kent and Medway 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 Kent and Medway CCG - this is only for commissioning and relates to both national and local flows.
and/or
•Patients treated by a provider where NHS Kent and Medway 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 NHS Kent and Medway CCG (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).
Dover District Council, Virtus, The Bunker and Daisy Group do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Microsoft Limited provide Cloud Services for South Central and West Commissioning Support Unit, Liaison Financial Services Ltd and Outcomes Based Healthcare 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.
ANS Group Limited will be assisting in the set up and management of the South Central and West Commissioning Support Unit Microsoft Azure Cloud and are therefore listed as a data processor. They will not have any additional processing / storage addresses (as these will be the Microsoft Azure addresses). Using the data for any other purpose would be considered a breach of this agreement.
University Hospitals Bristol NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
INVOICE VALIDATION - undertaken in-house by NHS Kent and Medway CCG.
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 HS Kent and Medway CCG.
3. The CEfF also receive backing data from the provider.
4. HS Kent and Medway CCG 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 HS Kent and Medway CCG CEfF team and the provider
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 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 - Prescribing Services Ltd
1. Identifiable SUS+ data is transferred from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to Prescribing Services Ltd, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd,.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd, 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) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
20. Adult Social Care
Data Processor 1 and 2 – NHS Kent and Medway CCG / HISbi (Hosted by Maidstone and Tunbridge Wells NHS Trust)
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), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data only is securely transferred from the DSCRO to NHS Kent and Medway CCG / HISbi using the MedeAnalytics pseudonymisation tool.
2) NHS Kent and Medway CCG / HISbi also receive the following pseudonymised data from providers that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
o Community Data
o Mental Health Data
o Social Care Data
o GP Data
o Any Qualified Provider data
3) NHS Kent and Medway CCG / HISbi also receive data from MedeAnalytics
4) NHS Kent and Medway CCG / HISbi provider data warehousing
5) NHS Kent and Medway CCG provide analysis to
o Data integration
o Undertake population health management
6) Allowed linkage is between data sets in point 1 and 2.
7) NHS Kent and Medway CCG / HISbi then transfer the data to MedeAnalytics.
8) Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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
HISbi hold and process identifiable data on behalf of a number of organisations so safeguards will be implemented to prevent re-identification of data through use of seperate logins. Local patient ID is required to flow to HISbi as they package the data before this is sent to MedeAnalytics and is needed by the CCG to challenge data submissions with the relevant provider. The identifiable key to the local patient id (which Maidstone and Tunbridge Wells NHS Trust hold) will be held separately in the organisation, preventing any possible re-identification from inclusion of this field.
In regard to the data being passed to MedeAnalytics on behalf of Kent and Medway CCG it is twofold. Firstly, for each dataset there is a pseudonymised table of data and, secondly, there is an encrypted mapping table. This data is created using the MedeAnalytics Pseudonymisation at Source tool which has been signed off by NHS Digital for use with NHS data in this way. The encrypted mapping table is used by MedeAnalytics in conjunction with a third party escrow for re-identification purposes in line with their contract with Kent and Medway CCG. Neither MedeAnalytics, HISbi or the third party have the ability to re-identify any of the patients included in either the pseudonymised data table or the encrypted mapping table. This, in conjunction with the separate logins being put in place, will ensure no re-identification of patient data takes place within the Kent and Medway Data Warehouse environment.
Data Processor 3 – MedeAnalytics
Data quality management and pseudonymisation is completed within the DSCRO using the MedeAnalytics tool specific to the CCG and is then disseminated as follows:
1) Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI) ,Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care only is securely transferred from the DSCRO/NHS Kent and Medway CCG/HISbi to MedeAnalytics using the MedeAnalytics pseudonymisation tool.
2) MedeAnalytics also receives the following pseudonymised data from NHS Kent and Medway CCG / HISbi that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
o Community Data
o Mental Health Data
o Social Care Data
o GP Data
o Any Qualified Provider data
3) MedeAnalytics add derived fields, link data and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning
o Check recorded activity against contracts or invoices and facilitate discussions with providers
o Undertake population health management
o Undertake data quality and validation checks
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
4) Allowed linkage is between the data sets contained within point 1 and point 2 only.
5) MedeAnalytics then pass the processed, pseudonymised and linked data to NHS Kent and Medway CCG / HISbi.
6) Aggregation of required data for CCG management use will be completed by MedeAnalytics 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.
Data Processor 4 - Outcomes Based Healthcare Ltd
1. SUS+, Maternity data (MSDS) and Mental Health data (MHSDS, MHMDS, MHLDDS) only is pseudonymised using an open pseudonymisation tool and shared key specific to this project and is securely transferred from the DSCRO to Outcomes Based Healthcare Ltd (this may be via South Central and West Commissioning Support Unit)
2. Outcomes Based Healthcare Ltd also receive GP data from providers that has been pseudonymised at source using the same open pseudonymisation tool and key specific to this project
3. Outcomes Based Healthcare Ltd link the data process the data to derive a OBH Segmentation Dataset (a patient-level dataset with pseudonymised NHS number)
4. Outcomes Based Healthcare Ltd provide analysis to the CCG through the online Outcomes Platform tool:
a. data quality and validation checks
b. understand patient journeys for pathway and service re-design, as well as recording the end results of care through outcome measurement
c. statistical process control
d. aggregate commissioning intelligence reports with small number suppression to named users in the CCG and providers commissioned by the CCG
5. Outcomes Based Healthcare Ltd transfer to the data to the CCG data warehouse (hosted by Maidstone and Tunbridge Wells NHS Trust)
6. South Central and West Commissioning Support Unit / DSCRO SCW will flow SUS data to the data warehouse to be linked to the post processed OBH data that is flowing in (4) above. (This is because the post-processed data from Outcomes Based Healthcare Ltd is a much reduced dataset and the CCG may want to link the OBH outputs to the wider SUS data)
7. Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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
Outcomes Based Healthcare Ltd will not have access to the pseudonymisation tool, which allows data to be pseudonymised using the Encryption key, therefore is unable to re-identify the data.
Data Processor 5 – HISbi, hosted by Maidstone and Tunbridge Wells NHS Trust
FOR OUTCOMES BASED HEALTHCARE (OBH) project
1. SUS+ and Mental Health data (MHSDS, MHMDS, MHLDDS, pseudonymised using an open pseudonymisation tool, is transferred from Outcomes Based Healthcare Ltd to Maidstone and Tunbridge Wells NHS Trust
2. Maidstone and Tunbridge Wells NHS Trust also receive a flow of SUS data from the DSCRO / South Central and West Commissioning Support Unit.
3. Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data under instruction of the CCG including:
a. Loading of data
b. Structuring of data
c. Data Quality
d. General queries
4. Local Patient ID will be pseudonymised before Maidstone and Tunbridge Wells NHS Trust have access to the data to prevent re-identification
5. The CCG will access the Maidstone and Tunbridge Wells NHS Trust servers to access the data
6. Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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 would repeat the exercise 2-3 years later
7. CCGs could request reviews to be done more frequently
8. SUS+ would only be requested each time a review was completed, and could be 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. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care
30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
Version 2.1 Additional Outputs
1. Outcomes Platform access via secure login (available to named individuals in the CCG and CCG commissioned providers only)
a. Aggregated monthly values for each outcome (with small number suppression, for any values under 8).
i. This enables the CCG and providers to visualise baselines using historical data for each outcome, and set improvement trajectories
ii. Monitoring of outcomes on a monthly basis
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Deprivation breakdowns for each outcome measure
2. OBH Segmentation Dataset sent securely to CCG data warehouse
a. A pseudonymised patient-level dataset which include NHS pseudonym, and condition ‘flags’, demographic and geographic information for the last 4 years for the entire GP registered population of the CCG
Access by the CCG to aggregated commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
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 and health outcomes through more effective commissioning of services.
COMMISSIONING
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
19. Assists commissioners to make better decisions to support patients and drive changes in health care
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
23. Monitoring of entire population, as a pose to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
27. Understand admissions linked to overprescribing.
28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
29. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
30. Designing and implementing new payment models across health and adult social care
31. 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.
Version 2.1 Additional Benefits
1. Population segmentation and outcome measurement across the entire population produces data that looks at the end results of care, burden of disease and complications, and their severity, as well as system activity metrics, and a better understanding of the population through grouping people by need. Including analysis showing impact of deprivation on outcomes and quality of care
2. Outcomes and segmentation data across the entire population will support decision making around service transformation, integrated care, care planning, care coordination, and service delivery, with the focus on improving the outcomes
3. Outcomes and segmentation data supports quality process improvement within care pathways
4. Outcomes Platform can be accessed by stakeholders across the entire health system, including commissioners and providers to have a single, transparent view of outcomes data
5. Refocuses health system providers (including health and social care providers) to work in a more integrated way to reduce the burden of disease
6. Outcomes Platform enables commissioners and providers to compare whether their longer-term targets and improvement trajectories set for each outcome, have been met. Whilst allowing providers to focus their efforts on improving these outcomes, for specific population groups, over a period of years
Benefits reported so far
The CCG has recently published their annual report for 2020/21 - https://www.kentandmedwayccg.nhs.uk/application/files/5216/3283/6666/Annual_Report_with_accounts_and_VFM_-_website_version_AUDIT.pdf
A summary of that report can be found at - https://www.kentandmedwayccg.nhs.uk/application/files/8016/3283/7565/NHS_Kent_and_Medway_CCG_Annual_Report_Summary_2020-21.pdf
This report highlights the achievements made during the year, of which some would only have been achieved by using the data from NHS Digital.
Further information about other achievements and future priorities can be found within the 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 5 versions.
DARS-NIC-362255-K5D1H-v4.3 20 April 2022 to 19 April 2025
- Title
- DSfC - NHS Kent and Medway CCG - IV, RS & Comm
- 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-362255-K5D1H-v3.1
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2022-04-20 | |
| End date | 2025-04-19 |
Objective for processing
[4 paragraphs unchanged]
Invoice Validation will be conducted by
Optum Health Solutions UK Limited and
Liaison Financial Services
Ltd.
Ltd &
NHS Kent and Medway
CCG is taking in-house Invoice Validation services delivered by Optum Health Solutions UK Limited from 01/02/2022.
CCG.
[61 paragraphs unchanged]
Processing for commissioning will be conducted by MedeAnalytics International
Limited, Optum Health Solutions UK
Limited, NHS South Central and West Commissioning Support Unit, Maidstone and Tunbridge Wells NHS Trust and Outcomes Based Health Care
Limited.
Limited & NHS Kent and Medway CCG.
[1 paragraph unchanged]
Health Informatics Service Business Intelligence (HISbi), a semi-autonomous department hosted by Maidstone
[12 words unchanged]
including loading and structuring of the data, as well as data quality
checks. The intention is that they will replace the commissioning functions of Optum Health Solutions UK Limited. However, during this transition there is a need for a period of dual running. Once Optum Health Solutions UK Limited’s processing has been completed, they will be removed from the application and data destruction certificates will be submitted.
checks
Processing activities
[11 paragraphs 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.
Re-identification will be conducted either through the MedeAnalytics portal, which has been approved by NHS Digital
Additionally clinicians, made aware of a number of cases that they believe would need intervention may request re-identification
for
this purpose, or by the DSCRO. National data opt outs are not applied in these cases as they are 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:
[2 paragraphs unchanged]
Polypharmacy
re-identification
re-IDs
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.
The Re-identification process for direct care
via the DSCRO
is as follows:
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
[30 paragraphs unchanged]
Amazon Web Services provide cloud services for Optum Health Solutions (UK) Limited and are therefore listed as a 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.
[1 paragraph unchanged]
Microsoft Limited provide Cloud Services for South Central and West Commissioning Support Unit,
Optum Health Solutions (UK) Limited,
Liaison Financial Services Ltd and Outcomes Based Healthcare Limited and are therefore
[33 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[2 paragraphs unchanged]
INVOICE VALIDATION -
Optum Health Solutions UK Limited.
undertaken in-house by
NHS Kent and Medway
CCG is taking in-house Invoice Validation services delivered by Optum Health Solutions from 01/02/2022.
CCG.
[1 paragraph unchanged]
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in
Optum Health Solutions.
HS Kent and Medway CCG.
[1 paragraph unchanged]
4.
Optum Health Solutions
HS Kent and Medway CCG
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
Optum Health Solutions
HS Kent and Medway CCG
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.
provider
[52 paragraphs unchanged]
Data Processor 1 and 2 –
Optum Health Solutions UK Limited/
NHS Kent and Medway CCG /
HISbi (Hosted by Maidstone and Tunbridge Wells NHS Trust)
1) . Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS,
[71 words unchanged]
Adult Social Care data only is securely transferred from the DSCRO to
Optum Health Solutions UK Limited/HISbi
NHS Kent and Medway CCG / HISbi
using the MedeAnalytics pseudonymisation tool.
2)
Optum Health Solutions UK Limited/HISbi
NHS Kent and Medway CCG / HISbi
also
receives
receive
the following pseudonymised data from providers that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
[5 paragraphs unchanged]
3)
Optum Health Solutions UK Limited/HISbi
NHS Kent and Medway CCG / HISbi
also receive data from MedeAnalytics
4)
Optum Health Solutions UK Limited/HISbi
NHS Kent and Medway CCG / HISbi
provider data warehousing
5)
Optum Health Solutions
NHS Kent and Medway CCG
provide analysis to
[3 paragraphs unchanged]
7)
Optum Health Solutions UK Limited/HISbi
NHS Kent and Medway CCG / HISbi
then transfer the data to
the CCG or
MedeAnalytics.
[2 paragraphs unchanged]
In regard to the data being passed to MedeAnalytics on behalf of
[71 words unchanged]
in line with their contract with Kent and Medway CCG. Neither MedeAnalytics,
Optum,
HISbi or the third party have the ability to re-identify any of
[30 words unchanged]
patient data takes place within the Kent and Medway Data Warehouse environment.
[2 paragraphs unchanged]
1) Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[68 words unchanged]
(NHSBSA Data) and Adult Social Care only is securely transferred from the
DSCRO/Optum Health Solutions UK Limited/HISbi
DSCRO/NHS Kent and Medway CCG/HISbi
to MedeAnalytics using the MedeAnalytics pseudonymisation tool.
2) MedeAnalytics also receives the following pseudonymised data from
Optum Health Solutions UK Limited/HISbi
NHS Kent and Medway CCG / HISbi
that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
[14 paragraphs unchanged]
5) MedeAnalytics then pass the processed, pseudonymised and linked data to
the CCG/Optum Health Solutions UK Limited/HISbi.
NHS Kent and Medway CCG / HISbi.
[27 paragraphs unchanged]
Unchanged: Expected output, Expected measurable benefits, Benefits reported.
DARS-NIC-362255-K5D1H-v3.1 4 November 2021 to 3 November 2024
- Title
- DSfC - NHS Kent and Medway CCG - IV, RS & Comm
- 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-362255-K5D1H-v2.4
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2021-11-04 | |
| End date | 2024-11-03 |
Objective for processing
[4 paragraphs unchanged]
Invoice Validation will be conducted by Optum Health Solutions
UK Limited
and Liaison Financial Services
Ltd
Ltd. NHS Kent and Medway CCG is taking in-house Invoice Validation services delivered by Optum Health Solutions UK Limited from 01/02/2022.
[3 paragraphs unchanged]
To conduct risk stratification, Secondary User Services (SUS+)
and Mental Health Services Dataset (MHSDS)
data, identifiable at the level of NHS number is linked with Primary
[50 words unchanged]
also enables General Practitioners (GPs) to better target intervention in Primary Care.
[42 paragraphs unchanged]
• Using value as the redesign principle
[17 paragraphs unchanged]
Health Informatics Service Business Intelligence (HISbi), a semi-autonomous department hosted by
Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data including loading and structuring of the data, as well as data quality
checks
checks. The intention is that they will replace the commissioning functions of Optum Health Solutions UK Limited. However, during this transition there is a need for a period of dual running. Once Optum Health Solutions UK Limited’s processing has been completed, they will be removed from the application and data destruction certificates will be submitted.
Processing activities
[11 paragraphs unchanged]
There is no requirement for the analytical teams to re-identify patients, but
[29 words unchanged]
local authority direct care staff only for the purpose of direct care.
All re-id requests
Re-identification
will be
processed and authorised
conducted either through the MedeAnalytics portal, which has been approved by NHS Digital for this purpose, or
by the
DSCRO on a case by case basis.
DSCRO.
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.
[3 paragraphs unchanged]
Polypharmacy
re-IDs
re-identification
[1 paragraph unchanged]
The Re-identification process for direct care
via the DSCRO
is as follows:
[6 paragraphs unchanged]
MEDEANALYTICS RE-ID
The Re-identification process for direct care via MedeAnalytics is as follows:
[19 paragraphs unchanged]
and/or
•Patients treated by a provider where NHS Kent and Medway CCG has joint responsibility for the provider services in the local health economy – this is only for Ambulance Trust data
[9 paragraphs unchanged]
SunGard Availability Services,
Dover District Council, Virtus, The Bunker and Daisy Group do not access
[28 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[3 paragraphs unchanged]
INVOICE VALIDATION - Optum Health Solutions UK
Limited
Limited. NHS Kent and Medway CCG is taking in-house Invoice Validation services delivered by Optum Health Solutions from 01/02/2022.
[62 paragraphs unchanged]
Data Processor 1 – MedeAnalytics
Data Processor 1 and 2 – Optum Health Solutions UK Limited/ HISbi (Hosted by Maidstone and Tunbridge Wells NHS Trust)
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), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data only is securely transferred from the DSCRO to Optum Health Solutions UK Limited/HISbi using the MedeAnalytics pseudonymisation tool.
2) Optum Health Solutions UK Limited/HISbi also receives the following pseudonymised data from providers that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
o Community Data
o Mental Health Data
o Social Care Data
o GP Data
o Any Qualified Provider data
3) Optum Health Solutions UK Limited/HISbi also receive data from MedeAnalytics
4) Optum Health Solutions UK Limited/HISbi provider data warehousing
5) Optum Health Solutions provide analysis to
o Data integration
o Undertake population health management
6) Allowed linkage is between data sets in point 1 and 2.
7) Optum Health Solutions UK Limited/HISbi then transfer the data to the CCG or MedeAnalytics.
8) Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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
HISbi hold and process identifiable data on behalf of a number of organisations so safeguards will be implemented to prevent re-identification of data through use of seperate logins. Local patient ID is required to flow to HISbi as they package the data before this is sent to MedeAnalytics and is needed by the CCG to challenge data submissions with the relevant provider. The identifiable key to the local patient id (which Maidstone and Tunbridge Wells NHS Trust hold) will be held separately in the organisation, preventing any possible re-identification from inclusion of this field.
In regard to the data being passed to MedeAnalytics on behalf of Kent and Medway CCG it is twofold. Firstly, for each dataset there is a pseudonymised table of data and, secondly, there is an encrypted mapping table. This data is created using the MedeAnalytics Pseudonymisation at Source tool which has been signed off by NHS Digital for use with NHS data in this way. The encrypted mapping table is used by MedeAnalytics in conjunction with a third party escrow for re-identification purposes in line with their contract with Kent and Medway CCG. Neither MedeAnalytics, Optum, HISbi or the third party have the ability to re-identify any of the patients included in either the pseudonymised data table or the encrypted mapping table. This, in conjunction with the separate logins being put in place, will ensure no re-identification of patient data takes place within the Kent and Medway Data Warehouse environment.
Data Processor 3 – MedeAnalytics
[1 paragraph unchanged]
1) Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[68 words unchanged]
(NHSBSA Data) and Adult Social Care only is securely transferred from the
DSCRO
DSCRO/Optum Health Solutions UK Limited/HISbi
to MedeAnalytics using the MedeAnalytics pseudonymisation tool.
2) MedeAnalytics also receives the following pseudonymised data from
providers
Optum Health Solutions UK Limited/HISbi
that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
[14 paragraphs unchanged]
5) MedeAnalytics then pass the processed, pseudonymised and linked data to the
CCG.
CCG/Optum Health Solutions UK Limited/HISbi.
[2 paragraphs unchanged]
8) MedeAnalytics also pass pseudonymised data listed in points 1 and 2 to Optum Health Solutions UK Limited.
Data Processor 4 - Outcomes Based Healthcare Ltd
Data Processor 2 – Optum Health Solutions UK Limited
1. SUS+, Maternity data (MSDS) and Mental Health data (MHSDS, MHMDS, MHLDDS) only is pseudonymised using an open pseudonymisation tool and shared key specific to this project and is securely transferred from the DSCRO to Outcomes Based Healthcare Ltd (this may be via South Central and West Commissioning Support Unit)
1) 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), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data only is securely transferred from the DSCRO to Optum Health Solutions UK Limited using the MedeAnalytics pseudonymisation tool.
2) Optum Health Solutions UK Limited also receive data from MedeAnalytics (as per point 8 above)
3) Optum Health Solutions provide analysis to
o Data integration
o Undertake population health management
4) Allowed linkage is between data sets in point 1 and 2.
5) Optum then transfer the data to the CCG or MedeAnalytics.
6) Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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
For clarity: Optum Health Solutions UK Limited require data for more transformational Public Health facing tools such as Health Population Manager whereas MedeAnalytics will be dealing with the day to day more transactional (SUS, SLAM, MH, Community…) data feeds required for contracting and commissioning purposes.
MedeAnalytics outputs only (Direct Care only)
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management service that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
Only GP Practice users are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify, and can only access data to which they have rights under RBAC (which is CG/SIRO approved – within the CCG)
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.
Linked datasets will be accessed via the MedeAnalytics platform by Optum to produce aggregate reports from this data to support the PHM planning processes.
Data Processor 3 - Outcomes Based Healthcare Ltd
1. SUS+ and Mental Health data (MHSDS, MHMDS, MHLDDS) only is pseudonymised using an open pseudonymisation tool and shared key specific to this project and is securely transferred from the DSCRO to Outcomes Based Healthcare Ltd (this may be via South Central and West Commissioning Support Unit)
[11 paragraphs unchanged]
Data Processor
4 -
5 – HISbi, hosted by
Maidstone and Tunbridge Wells NHS Trust
1. SUS+ and Mental Health data (MHSDS, MHMDS, MHLDDS is transferred from Outcomes Based Healthcare Ltd to Maidstone and Tunbridge Wells NHS Trust
FOR OUTCOMES BASED HEALTHCARE (OBH) project
1. SUS+ and Mental Health data (MHSDS, MHMDS, MHLDDS, pseudonymised using an open pseudonymisation tool, is transferred from Outcomes Based Healthcare Ltd to Maidstone and Tunbridge Wells NHS Trust
[1 paragraph unchanged]
3. Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data under instruction of the CCG
including;
including:
[7 paragraphs unchanged]
Benefits reported
Not stated in the previous version; added here.
The CCG has recently published their annual report for 2020/21 - https://www.kentandmedwayccg.nhs.uk/application/files/5216/3283/6666/Annual_Report_with_accounts_and_VFM_-_website_version_AUDIT.pdf
A summary of that report can be found at - https://www.kentandmedwayccg.nhs.uk/application/files/8016/3283/7565/NHS_Kent_and_Medway_CCG_Annual_Report_Summary_2020-21.pdf
This report highlights the achievements made during the year, of which some would only have been achieved by using the data from NHS Digital.
Further information about other achievements and future priorities can be found within the report.
Unchanged: Expected output, Expected measurable benefits.
Objective for processing
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+), 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).
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by Optum Health Solutions UK Limited and Liaison Financial Services Ltd. NHS Kent and Medway CCG is taking in-house Invoice Validation services delivered by Optum Health Solutions UK Limited from 01/02/2022.
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 (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Ltd.
COMMISSIONING
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
- Adult Social Care
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
Provide intelligence about the safety and effectiveness of medicines.
Risk Stratification using pseudo data – using a tool for identifying pseudonymised patients at risk. The pseudonymised patient level data is then shared with health and care professionals with a legitimate relationship to the patient who are able to request re-identification when required for direct care purposes.
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population.
Provide intelligence about the safety and effectiveness of medicines.
Allow analysis of patient pathways across healthcare and social care.
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by MedeAnalytics International Limited, Optum Health Solutions UK Limited, NHS South Central and West Commissioning Support Unit, Maidstone and Tunbridge Wells NHS Trust and Outcomes Based Health Care Limited.
Outcomes Based Healthcare Limited will use pseudonymised data, to support population segmentation and measurement of outcomes, for population health management. This includes development of a segmentation model, outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of the CCG. This will enable near real-time outcome measurement for specific population segments, where the entire GP registered population is accounted for.
Health Informatics Service Business Intelligence (HISbi), a semi-autonomous department hosted by Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data including loading and structuring of the data, as well as data quality checks. The intention is that they will replace the commissioning functions of Optum Health Solutions UK Limited. However, during this transition there is a need for a period of dual running. Once Optum Health Solutions UK Limited’s processing has been completed, they will be removed from the application and data destruction certificates will be submitted.
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 would repeat the exercise 2-3 years later
7. CCGs could request reviews to be done more frequently
8. SUS+ would only be requested each time a review was completed, and could be 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. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care
30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
Version 2.1 Additional Outputs
1. Outcomes Platform access via secure login (available to named individuals in the CCG and CCG commissioned providers only)
a. Aggregated monthly values for each outcome (with small number suppression, for any values under 8).
i. This enables the CCG and providers to visualise baselines using historical data for each outcome, and set improvement trajectories
ii. Monitoring of outcomes on a monthly basis
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Deprivation breakdowns for each outcome measure
2. OBH Segmentation Dataset sent securely to CCG data warehouse
a. A pseudonymised patient-level dataset which include NHS pseudonym, and condition ‘flags’, demographic and geographic information for the last 4 years for the entire GP registered population of the CCG
Access by the CCG to aggregated commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
Benefits reported
The CCG has recently published their annual report for 2020/21 - https://www.kentandmedwayccg.nhs.uk/application/files/5216/3283/6666/Annual_Report_with_accounts_and_VFM_-_website_version_AUDIT.pdf
A summary of that report can be found at - https://www.kentandmedwayccg.nhs.uk/application/files/8016/3283/7565/NHS_Kent_and_Medway_CCG_Annual_Report_Summary_2020-21.pdf
This report highlights the achievements made during the year, of which some would only have been achieved by using the data from NHS Digital.
Further information about other achievements and future priorities can be found within the report.
DARS-NIC-362255-K5D1H-v2.4 1 April 2021 to 31 March 2024
- Title
- DSfC - NHS Kent and Medway CCG - IV, RS & Comm
- 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-362255-K5D1H-v1.4
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
Datasets: + Adult Social Care
Objective for processing
[45 paragraphs unchanged]
- Adult Social Care
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.
[14 paragraphs unchanged]
Risk Stratification using pseudo data – using a tool for identifying pseudonymised patients at risk. The pseudonymised patient level data is then shared with health and care professionals with a legitimate relationship to the patient who are able to request re-identification when required for direct care purposes.
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population.
Provide intelligence about the safety and effectiveness of medicines.
Allow analysis of patient pathways across healthcare and social care.
[1 paragraph unchanged]
Processing for commissioning will be conducted by MedeAnalytics International
Limited and
Limited,
Optum Health Solutions UK
Limited
Limited, NHS South Central and West Commissioning Support Unit, Maidstone and Tunbridge Wells NHS Trust and Outcomes Based Health Care Limited.
Outcomes Based Healthcare Limited will use pseudonymised data, to support population segmentation and measurement of outcomes, for population health management. This includes development of a segmentation model, outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of the CCG. This will enable near real-time outcome measurement for specific population segments, where the entire GP registered population is accounted for.
Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data including loading and structuring of the data, as well as data quality checks
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
MEDEANALYTICS RE-ID
GP Practice staff are able to access de-identified data for patients registered to their own practice.
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
Only GP Practice users are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify have access to encrypted data, and can only access data to which they have rights under RBAC
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.
[22 paragraphs unchanged]
Microsoft Limited and
Amazon Web Services provide cloud services for Optum Health Solutions (UK) Limited and are therefore listed as
processors.
a processor.
They supply support to the system, but do not access data. Therefore,
[16 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[1 paragraph unchanged]
Microsoft Limited provide Cloud Services for South Central and West Commissioning Support Unit, Optum Health Solutions (UK) Limited, Liaison Financial Services Ltd and Outcomes Based Healthcare 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.
ANS Group Limited will be assisting in the set up and management of the South Central and West Commissioning Support Unit Microsoft Azure Cloud and are therefore listed as a data processor. They will not have any additional processing / storage addresses (as these will be the Microsoft Azure addresses). Using the data for any other purpose would be considered a breach of this agreement.
University Hospitals Bristol NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
[62 paragraphs unchanged]
20. Adult Social Care
[2 paragraphs unchanged]
1) Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[51 words unchanged]
e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI)
and Medicines
,Medicines
Dispensed in Primary Care (NHSBSA Data)
and Adult Social Care
only is securely transferred from the DSCRO to MedeAnalytics using the MedeAnalytics pseudonymisation tool.
[20 paragraphs unchanged]
1) 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS,
[50 words unchanged]
(PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator
(SHMI) and
(SHMI),
Medicines Dispensed in Primary Care (NHSBSA Data)
and Adult Social Care
data only is securely transferred from the DSCRO to Optum Health Solutions UK Limited using the MedeAnalytics pseudonymisation tool.
[14 paragraphs unchanged]
Data Processor 3 - Outcomes Based Healthcare Ltd
1. SUS+ and Mental Health data (MHSDS, MHMDS, MHLDDS) only is pseudonymised using an open pseudonymisation tool and shared key specific to this project and is securely transferred from the DSCRO to Outcomes Based Healthcare Ltd (this may be via South Central and West Commissioning Support Unit)
2. Outcomes Based Healthcare Ltd also receive GP data from providers that has been pseudonymised at source using the same open pseudonymisation tool and key specific to this project
3. Outcomes Based Healthcare Ltd link the data process the data to derive a OBH Segmentation Dataset (a patient-level dataset with pseudonymised NHS number)
4. Outcomes Based Healthcare Ltd provide analysis to the CCG through the online Outcomes Platform tool:
a. data quality and validation checks
b. understand patient journeys for pathway and service re-design, as well as recording the end results of care through outcome measurement
c. statistical process control
d. aggregate commissioning intelligence reports with small number suppression to named users in the CCG and providers commissioned by the CCG
5. Outcomes Based Healthcare Ltd transfer to the data to the CCG data warehouse (hosted by Maidstone and Tunbridge Wells NHS Trust)
6. South Central and West Commissioning Support Unit / DSCRO SCW will flow SUS data to the data warehouse to be linked to the post processed OBH data that is flowing in (4) above. (This is because the post-processed data from Outcomes Based Healthcare Ltd is a much reduced dataset and the CCG may want to link the OBH outputs to the wider SUS data)
7. Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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
Outcomes Based Healthcare Ltd will not have access to the pseudonymisation tool, which allows data to be pseudonymised using the Encryption key, therefore is unable to re-identify the data.
Data Processor 4 - Maidstone and Tunbridge Wells NHS Trust
1. SUS+ and Mental Health data (MHSDS, MHMDS, MHLDDS is transferred from Outcomes Based Healthcare Ltd to Maidstone and Tunbridge Wells NHS Trust
2. Maidstone and Tunbridge Wells NHS Trust also receive a flow of SUS data from the DSCRO / South Central and West Commissioning Support Unit.
3. Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data under instruction of the CCG including;
a. Loading of data
b. Structuring of data
c. Data Quality
d. General queries
4. Local Patient ID will be pseudonymised before Maidstone and Tunbridge Wells NHS Trust have access to the data to prevent re-identification
5. The CCG will access the Maidstone and Tunbridge Wells NHS Trust servers to access the data
6. Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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
[85 paragraphs unchanged] 29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care 30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care Version 2.1 Additional Outputs 1. Outcomes Platform access via secure login (available to named individuals in the CCG and CCG commissioned providers only) a. Aggregated monthly values for each outcome (with small number suppression, for any values under 8). i. This enables the CCG and providers to visualise baselines using historical data for each outcome, and set improvement trajectories ii. Monitoring of outcomes on a monthly basis b. Filtering of outcomes data by age bands, deprivation centiles, and other variables c. Statistical process control for each outcome measure d. Deprivation breakdowns for each outcome measure 2. OBH Segmentation Dataset sent securely to CCG data warehouse a. A pseudonymised patient-level dataset which include NHS pseudonym, and condition ‘flags’, demographic and geographic information for the last 4 years for the entire GP registered population of the CCG Access by the CCG to aggregated commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
Expected measurable benefits
[72 paragraphs unchanged] 29. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care 30. Designing and implementing new payment models across health and adult social care 31. 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. Version 2.1 Additional Benefits 1. Population segmentation and outcome measurement across the entire population produces data that looks at the end results of care, burden of disease and complications, and their severity, as well as system activity metrics, and a better understanding of the population through grouping people by need. Including analysis showing impact of deprivation on outcomes and quality of care 2. Outcomes and segmentation data across the entire population will support decision making around service transformation, integrated care, care planning, care coordination, and service delivery, with the focus on improving the outcomes 3. Outcomes and segmentation data supports quality process improvement within care pathways 4. Outcomes Platform can be accessed by stakeholders across the entire health system, including commissioners and providers to have a single, transparent view of outcomes data 5. Refocuses health system providers (including health and social care providers) to work in a more integrated way to reduce the burden of disease 6. Outcomes Platform enables commissioners and providers to compare whether their longer-term targets and improvement trajectories set for each outcome, have been met. Whilst allowing providers to focus their efforts on improving these outcomes, for specific population groups, over a period of years
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 able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+), 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).
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by Optum Health Solutions 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 (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Ltd.
COMMISSIONING
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
- Adult Social Care
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
• 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
Provide intelligence about the safety and effectiveness of medicines.
Risk Stratification using pseudo data – using a tool for identifying pseudonymised patients at risk. The pseudonymised patient level data is then shared with health and care professionals with a legitimate relationship to the patient who are able to request re-identification when required for direct care purposes.
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population.
Provide intelligence about the safety and effectiveness of medicines.
Allow analysis of patient pathways across healthcare and social care.
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by MedeAnalytics International Limited, Optum Health Solutions UK Limited, NHS South Central and West Commissioning Support Unit, Maidstone and Tunbridge Wells NHS Trust and Outcomes Based Health Care Limited.
Outcomes Based Healthcare Limited will use pseudonymised data, to support population segmentation and measurement of outcomes, for population health management. This includes development of a segmentation model, outcomes, and baselining and monitoring of individual outcomes on the Outcomes Framework, as well as providing detailed analysis relating to those outcomes, on behalf of the CCG. This will enable near real-time outcome measurement for specific population segments, where the entire GP registered population is accounted for.
Maidstone and Tunbridge Wells NHS Trust will conduct general processing of the data including loading and structuring of the data, as well as data quality checks
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 would repeat the exercise 2-3 years later
7. CCGs could request reviews to be done more frequently
8. SUS+ would only be requested each time a review was completed, and could be 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. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care
30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care
Version 2.1 Additional Outputs
1. Outcomes Platform access via secure login (available to named individuals in the CCG and CCG commissioned providers only)
a. Aggregated monthly values for each outcome (with small number suppression, for any values under 8).
i. This enables the CCG and providers to visualise baselines using historical data for each outcome, and set improvement trajectories
ii. Monitoring of outcomes on a monthly basis
b. Filtering of outcomes data by age bands, deprivation centiles, and other variables
c. Statistical process control for each outcome measure
d. Deprivation breakdowns for each outcome measure
2. OBH Segmentation Dataset sent securely to CCG data warehouse
a. A pseudonymised patient-level dataset which include NHS pseudonym, and condition ‘flags’, demographic and geographic information for the last 4 years for the entire GP registered population of the CCG
Access by the CCG to aggregated commissioning intelligence is governed by the organisation employee code of practice, data protection policies and information governance protocols.
DARS-NIC-362255-K5D1H-v1.4 1 April 2021 to 31 March 2024
- Title
- DSfC - NHS Kent and Medway CCG - IV, RS & Comm
- 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-362255-K5D1H-v0.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Title | DSfC - NHS Kent and Medway CCG - IV, RS & Comm | |
| Start date | 2021-04-01 | |
| End date | 2024-03-31 | |
| 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'. |
Datasets: + Medicines dispensed in Primary Care (NHSBSA data); + Personal Demographic Service; + Summary Hospital-level Mortality Indicator (SHMI); + e-Referral Service for Commissioning
Objective for processing
[2 paragraphs unchanged]
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,
(SUS+),
which is received into a secure Controlled Environment for Finance (CEfF). The
[13 words unchanged]
is only used to confirm the accuracy of backing-data sets (data from
providers) and will not be used further.
providers).
[1 paragraph unchanged]
Invoice Validation will be conducted by Optum Health Solutions and Liaison Financial
Services.
Services Ltd
[1 paragraph unchanged]
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Ltd.
[4 paragraphs unchanged]
•
-
Secondary Uses Service (SUS+)
•
-
Local Provider Flows
[12 paragraphs unchanged]
•
-
Mental Health Minimum Data Set (MHMDS)
•
-
Mental Health Learning Disability Data Set (MHLDDS)
•
-
Mental Health Services Data Set (MHSDS)
•
-
Maternity Services Data Set (MSDS)
•
-
Improving Access to Psychological Therapy (IAPT)
•
-
Child and Young People Health Service (CYPHS)
•
-
Community Services Data Set (CSDS)
•
-
Diagnostic Imaging Data Set (DIDS)
•
-
National Cancer Waiting Times Monitoring Data Set (CWT)
•
-
Civil Registries Data (CRD) (Births)
•
-
Civil Registries Data (CRD) (Deaths)
•
-
National Diabetes Audit (NDA)
•
-
Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
[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
Provide intelligence about the safety and effectiveness of medicines.
[1 paragraph unchanged]
Processing for commissioning will be conducted by MedeAnalytics International Limited and Optum Health Solutions
UK Limited
Processing activities
[7 paragraphs unchanged]
The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.
[16 paragraphs unchanged]
For the purpose of Risk Stratification:
• Patients who are normally registered and/or resident within NHS Kent and Medway CCG (including historical activity where the patient was previously registered or resident in another commissioner
[6 paragraphs unchanged]
Microsoft
UK supply IT infrastructure
Limited and Amazon Web Services provide cloud services for Optum Health Solutions (UK) Limited
and are therefore listed as
a data processor.
processors.
They supply support to the system, but do not access data. Therefore,
[16 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
SunGard Availability Services, Dover District Council,
Virtus
Virtus, The Bunker
and Daisy Group 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.
INVOICE VALIDATION - Optum Health Solutions
UK Limited
[21 paragraphs unchanged]
RISK STRATIFICATION - Prescribing Services Ltd
1. Identifiable SUS+ data is transferred from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to Prescribing Services Ltd, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd,.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd, has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level
[29 paragraphs unchanged]
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
[2 paragraphs unchanged]
1) Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[38 words unchanged]
(Births and Deaths), National Diabetes Audit (NDA) and Patient Reported Outcome Measures
(PROMs)
(PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI) and Medicines Dispensed in Primary Care (NHSBSA Data)
only is securely transferred from the DSCRO to
MedeAnalytics.
MedeAnalytics using the MedeAnalytics pseudonymisation tool.
[18 paragraphs unchanged]
8) MedeAnalytics also pass pseudonymised
SUS+
data listed in points 1
and
GP data
2
to Optum Health
Solutions.
Solutions UK Limited.
Data Processor 2 – Optum Health Solutions
UK Limited
9) Optum Health Solutions provide analysis to
1) 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), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI) and Medicines Dispensed in Primary Care (NHSBSA Data) data only is securely transferred from the DSCRO to Optum Health Solutions UK Limited using the MedeAnalytics pseudonymisation tool.
2) Optum Health Solutions UK Limited also receive data from MedeAnalytics (as per point 8 above)
3) Optum Health Solutions provide analysis to
[2 paragraphs unchanged]
10) Aggregation of data is completed by Optum Health Solutions.
4) Allowed linkage is between data sets in point 1 and 2.
11) Patient level data will not be shared outside of Optum Health Solutions and will only be shared within Optum Health Solutions 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
5) Optum then transfer the data to the CCG or MedeAnalytics.
For clarity: Optum require data for more transformational Public Health facing tools such as Health Population Manager whereas MedeAnalytics will be dealing with the day to day more transactional (SUS, SLAM, MH, Community…) data feeds required for contracting and commissioning purposes.
6) Patient level data will not be shared outside of the CCG and its processors and will only be shared within 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
For clarity: Optum Health Solutions UK Limited require data for more transformational Public Health facing tools such as Health Population Manager whereas MedeAnalytics will be dealing with the day to day more transactional (SUS, SLAM, MH, Community…) data feeds required for contracting and commissioning purposes.
[5 paragraphs unchanged]
Linked datasets will be accessed via the MedeAnalytics platform by Optum to produce aggregate reports from this data to support the PHM planning processes.
Expected output
[16 paragraphs unchanged] 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. [40 paragraphs unchanged] 19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand. 20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals. 22. Allow Commissioners to better protect or improve the public health of the total local patient population 23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population 24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 25. Investigate mortality outcomes for trusts. 26. Identify medication prescribing trends and their effectiveness. 27. Linking prescribing habits to entry points into the health and social care system 28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
Expected measurable benefits
[19 paragraphs unchanged] 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 and health outcomes through more effective commissioning of services. [34 paragraphs unchanged] 18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 19. Assists commissioners to make better decisions to support patients and drive changes in health care 20. Allows comparisons of providers performance to assist improvement in services – increase the quality 21. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 23. Monitoring of entire population, as a pose to only those that engage with services 24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice. 25. Monitor the quality and safety of the delivery of healthcare services. 26. Allow focused commissioning support based on factual data rather than assumed and projected sources 27. Understand admissions linked to overprescribing. 28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
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 able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+), 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).
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by Optum Health Solutions 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 (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) and Mental Health Services Dataset (MHSDS) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Ltd.
COMMISSIONING
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
Provide intelligence about the safety and effectiveness of medicines.
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by MedeAnalytics International Limited and Optum Health Solutions UK Limited
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 would repeat the exercise 2-3 years later
7. CCGs could request reviews to be done more frequently
8. SUS+ would only be requested each time a review was completed, and could be 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. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
DARS-NIC-362255-K5D1H-v0.2 1 April 2020 to 31 March 2023
- Title
- DSfC - NHS Kent and Medway CCG - IV, Comm
- 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 will be conducted by Optum Health Solutions 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.
COMMISSIONING
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
• Secondary Uses Service (SUS+)
• Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
• Mental Health Minimum Data Set (MHMDS)
• Mental Health Learning Disability Data Set (MHLDDS)
• Mental Health Services Data Set (MHSDS)
• Maternity Services Data Set (MSDS)
• Improving Access to Psychological Therapy (IAPT)
• Child and Young People Health Service (CYPHS)
• Community Services Data Set (CSDS)
• Diagnostic Imaging Data Set (DIDS)
• National Cancer Waiting Times Monitoring Data Set (CWT)
• Civil Registries Data (CRD) (Births)
• Civil Registries Data (CRD) (Deaths)
• National Diabetes Audit (NDA)
• Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to highlight patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by MedeAnalytics International Limited and Optum Health Solutions
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 would repeat the exercise 2-3 years later
7. CCGs could request reviews to be done more frequently
8. SUS+ would only be requested each time a review was completed, and could be requested at different times as independent reviews
COMMISSIONING
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Benefits reported
Yielded Benefits is not a requirement for new applications.
Register history
When this agreement appeared in, or was edited in, each monthly edition of the register. Built by comparing every edition this site holds, the earliest of which is July 2021.
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July 2021 —
already listed in the earliest edition this site holds, so it may be older. 2 versions: DARS-NIC-362255-K5D1H-v0.2, DARS-NIC-362255-K5D1H-v1.4
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November 2021
1 version added: DARS-NIC-362255-K5D1H-v2.4
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January 2022
1 version added: DARS-NIC-362255-K5D1H-v3.1
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July 2022
1 version added: DARS-NIC-362255-K5D1H-v4.3
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October 2022
Succeeded Applicant organisation: NHS Kent and Medway CCG succeeded by NHS Kent and Medway ICB from 1 July 2022, according to NHS ODS. Not counted as a change.Succeeded Data controllers: NHS Kent and Medway CCG succeeded by NHS Kent and Medway 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-362255-K5D1H-v0.2 — Datasets: legal basis: “
s261(1) and” taken out. Made to 639 agreements in this edition, so it is reported once, on the changes page, and not counted as an amendment of this agreement.
Cite this page
NHS England (2026) Data Uses Register, September 2026 edition, agreement DARS-NIC-362255-K5D1H, “DSfC - NHS Kent and Medway CCG - IV, RS & Comm”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-362255-k5d1h/ (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-362255-K5D1H to see the original rows.