DSfC - NHS Oxfordshire CCG and Oxfordshire County Council; Comm.
NHS Buckinghamshire, Oxfordshire and Berkshire West ICB · Sub ICB Location
Listed under NHS Thames Valley Integrated Care Board.
Expired The latest version ended on 16 June 2025. The September 2026 register still lists the agreement, but its term has passed.
- Reference
- DARS-NIC-116582-F2F2J
- Latest version
- v11.4
- Term of latest version
- 17 June 2022 to 16 June 2025
- Start date
- Before 6 August 2019
- Data controller
- Joint Data Controller
- Commercial purposes
- No
- Sublicensing
- No
- Files released to date
- 0
Data controllers
Why the data was released
Objective for processing
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the Oxfordshire area.
The Clinical Commissioning Group (CCG) and Local Authority 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 CCG and Local Authority are also part of a programme that focuses on population health management that aims to improve healthcare of the local population through focusing on specific activities.
The CCG and Council are setting up a Joint Commissioning team, where most of the team will be employed by the Council but will obviously need access to the same health data as CCG colleagues to enable the whole team to fulfil their Commissioning team functions. This is also in preparation for being part of the same Integrated Care System.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
- Adult Social Care data
Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.
Processing of Adult Social Care data is only permitted for the Commissioning purposes set out within this agreement. Adult Social Care data will not be processed for the purpose of Risk Stratification.
The pseudonymised data is required to for the following purposes:
- Population health management:
o Understanding the interdependency of care services
o Targeting care more effectively
- Data Quality and Validation – allowing data quality checks on the submitted data
- Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
- Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
- Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
- Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
- Service redesign
- Health Needs Assessment – identification of underlying disease prevalence within the local population
- Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
- Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
- Support measuring the health, mortality or care needs of the total local population
- Provide intelligence about the safety and effectiveness of medicines.
- Allow analysis of patient pathways across healthcare and social care.
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by South Central and West Commissioning Support Unit, Oxfordshire University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust, and University of Oxford-Medical Sciences Division-Nuffield Department of Primary Care Health Services.
Each of the Data Processors specified above has a distinct set task, and there is no duplication of effort.
Oxfordshire’s Suspected CANcer (SCAN) pathway evaluation
University of Oxford - Medical Sciences Division - Nuffield Department of Primary Care Health Sciences
Cancer is the leading cause of premature death in the UK and cancer patients have lower survival rates than comparable health economies. One explanation for the survival deficit is diagnostic delay. ‘Two-week-wait’ referral pathways were introduced to enable the urgent investigation of NHS patients with specific “red-flag” symptoms. As a consequence patients with Non-specific but Concerning Symptoms (NSCS) became ineligible for rapid investigation despite half of all cancer patients presenting with NSCS. These patients wait longer for referral and for a cancer diagnosis and are often diagnosed at a later stage when curative treatment is no longer an option. To address this problem, the Accelerate Coordinate Evaluate (ACE) programme was established to pilot rapid diagnostic pathways to detect cancer in patients with NSCS. This new ACE programme of work is funded by Cancer Research UK (CRUK) and National Health Service England (NHSE).
Ten NSCS pathways have been piloted in five NHS localities by Wave 2/second round of the ACE programme, and the Suspected CANcer (SCAN) pathway in Oxfordshire is one of them. Oxfordshire’s SCAN pathway is the only one to perform a CT scan first on all patients accepted for investigation.
NHS Oxfordshire CCG now wishes to evaluate the outcomes of patients referred to the SCAN pathway for investigation of a pre-specified set of symptoms compared to the outcomes of patients with the same symptoms investigated through existing routes to cancer diagnosis in Oxfordshire before and while the SCAN pathway was available. The results of the analysis will also help support the planned national rollout of similar vague symptoms pathways.
A comparator cohort dataset from SUS, CWT, Local Provider flows and GP data will be used to compare the SCAN cohort against, and to establish whether providing GPs with a dedicated pathway through which patients with low-risk but not no-risk symptoms can be investigated has reduced the time from initial primary care presentation to diagnosis, while matching or exceeding the diagnostic yield of pre-existing routes to cancer diagnosis for these patients.
Pilot Programme
Due to increasing demand on services, the CCG is constantly attempting to find new ways to improve the services that it commissions. One of the key issues is that patient pathways can span multiple secondary care services, each operated by different secondary care organisations. The NHS England 5 year forward plan is an attempt to tackle this complication by encouraging a more joined up approach to a patient’s care. In order to deliver on this in the current NHS structure, the CCG has proposed to engage 3 NHS Foundations Trusts (Oxford University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust) as data processors.
They will be given access to the pseudonymised data in order to:
• analyse and investigate patients across pathways of care
• to identify healthcare consumption and capacity issues
• understand the interdependency of care services
• look at demand management and service redesign.
The expectation is that this agreement will be superseded by the approval of anew Data Sharing Agreement (DSA) following the CCG's transition into an ICB. The appropriate data flows will be transferred to this new agreement.
Processing activities
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role 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. The data to be released from NHS Digital will not be national data.
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)
Onward Sharing
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 are;
· GPs have requested a list of patients registered with them who have depression, obesity, are on a waiting list, and aged 20-64. This is in order to assist them with direct patient care interventions for these patients to improve the outcomes using the existing services. The patient will benefit from an additional and more personalised support package and enhanced access to support. Any lessons learnt will also enable them to make changes to strengthen the patient pathway to others with the same conditions.
· GPs have requested a list of patients registered with them who are adolescents between the age of 15 – 24 who are asthmatic and have a mental health diagnosis. This is in order to assist them with direct patient care interventions for these patients to improve the outcomes using the existing services. The patient will benefit from an additional and more personalised support package and enhanced access to support. Any lessons learnt will also enable them to make changes to strengthen the patient pathway to others with the same conditions.
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. Consideration of identifying the patient cohort will be two-fold, from both a clinical commissioning perspective and a data led perspective. The process will be followed on a programmatic basis or, rarely, individual / small cohorts.
2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSU’s Business Intelligence (BI) Tool, or through a manual form.
3. The DSCRO assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system.
4. For automated systems, steps 1 - 3 wouldn’t apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without further checks.
5. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or Care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
6. DSCROs retain an audit trail of all re-id requests
Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.
Segregation
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.
Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.
All access to data is auditable by NHS Digital.
Data 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 Oxfordshire CCG (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where NHS Oxfordshire 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 Oxfordshire CCG - this is only for commissioning and relates to both national and local flows.
and/or
• Patients treated by a provider where NHS Oxfordshire CCG has joint responsibility for the provider services in the local health economy – this is only for Ambulance Trust data
and/or
• The population for which Oxfordshire County Council has responsibility for.
In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement.
A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting
Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation).
Microsoft Limited provide Cloud Services for NHS North of England Commissioning Support Unit, North East London Commissioning Support Unit, Optum Health Solutions UK Limited and South Central and West Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Amazon Web Services provide Cloud Services for Optum Health Solutions UK Limited and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Pulsant, IT Professional Services Ltd, Interxion, Ark Data Centres and 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.
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
Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
12. Civil Registries Data (CRD) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
20. Adult Social Care data
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – NHS South, Central and West Commissioning Support Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS) data, Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data only is held within the DSCRO until the completion of points 2-8.
2. NHS South, Central and West Commissioning Support Unit receives GP Data as follows:
a. Identifiable GP data is submitted to NHS South, Central and West Commissioning Support Unit.
b. The identifiable data lands in a ring-fenced area for GP data only.
c. The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
d. There is a Data Processing Agreement in place between the GP and NHS South, Central and West Commissioning Support Unit. A specific named individual with NHS South, Central and West Commissioning Support Unit acts on behalf of the GP. This person has access to a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box. This software cannot be interrogated.
e. The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to that GP and to that specific date.
f. Identifiable data will only be processed by substantive employees of the data controller and processors. Before the CSU will receive the data from the ring fenced area, they require confirmation that the identifiable data has been deleted.
g. The CSU are then sent the pseudonymised GP data (into Database 2) with the pseudo algorithm specific to them.
h. Pseudonymised GP data is then linked to pseudonymised SUS data and an algorithm applied, also used for risk stratification. The outputs are then sent to Database 1.
3. NHS South, Central and West Commissioning Support Unit also receives a flow of social care data. Social Care data is received in one of the following 2 ways:
- Identifiable
a. Identifiable Social Care data is submitted to NHS South, Central and West Commissioning Support Unit.
b. The identifiable data lands in a ring-fenced area for Social Care data.
c. The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
d. There is a Data Processing Agreement in place between the Local Authority and NHS South, Central and West Commissioning Support Unit. A specific named individual with NHS South, Central and West Commissioning Support Unit acts on behalf of the Local Authority. This person has access to a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box. This software cannot be interrogated.
e. The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to that Local Authority and to that specific date.
f. Identifiable data will only be processed by substantive employees of the data controller and processors. Before the CSU will receive the data from the ring fenced area, they require confirmation that the identifiable data has been deleted.
g. The CSU are then sent the pseudonymised social care data with the pseudo algorithm specific to them.
- Pseudonymised
a. The Social Care organisation is issued with their own black box solution.
b. The social care organisation requests a pseudonymisation key from the DSCRO. The key can only be used once is specific date to that date. The DSCRO is not involved in the processing of personal data for the purpose of pseudonymisation of social care data.
c. There is a Data Processing Agreement in place between the Provider and SCW CSU. A specific named individual with SCW CSU acts on behalf of the Provider.
d. The social care organisation submit the pseudonymised social care data to the CSU with the pseudo algorithm specific to them.
4. Once the pseudonymised GP and social care data is received, the CSU make a request to the DSCRO.
5. The DSCRO checks the dates of the key generation (Point 2e & 3e/3b).
6. The DSCRO then sends a mapping table to the CSU.
7. The CSU then overwrite the organisation specific keys with the DSCRO key.
8. The mapping table is then deleted.
9. The pseudonymised data in point 1 is securely transferred from the DSCRO to NHS South, Central and West CSU.
10. Social care data and the outputs from Database 2 and GP data is then linked to the datasets listed within point 1.
11. NHS South, Central and West Commissioning Support Unit add derived fields, link data sets and provide analysis to.
a. See patient journeys for pathways or service design, re-design and de-commissioning
b. Check recorded activity against contracts or invoices and facilitate discussions with providers
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
12. Allowed linkage is between the data sets contained within point 1, point 2 and point 3 and point 4. No further linkage is permitted.
13. NHS South, Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG and Local Authority
14. Aggregation of required data for CCG and Local Authority management use will be completed by NHS South, Central and West Commissioning Support Unit or the CCG/Local Authority as instructed by the CCG/Local Authority.
15. Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority 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 2 - Optum Health Solutions (UK) Ltd - for the NHS England second round/Wave 2 PHM project
1) Pseudonymised SUS+, Mental Health Services Data Set (MHSDS), Community Services Data Set (CSDS), Local Provider data flows, GP Primary Care Data and Social Care Data is securely transferred from NHS Oxfordshire CCG to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national datasets and sent as individual data flows.
2) Optum Health Solutions (UK) Ltd provide analysis to:
o Whole population segmentation to assess population health needs
o Prospective risk scoring for individuals to indicate the likelihood of future adverse events
o Predictive modelling to determine individuals at risk and an understanding of the drivers of risk
o Longitudinal analysis of intersegmental drift - identifying individuals who move between complexity classifications and the drivers of these transitions
o The production of individual-level theographs to identify gaps in care
3) Allowed linkage is between the datasets contained with point (1) above. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and Local Provider Flows which contain only secondary care activity.
4) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG and Local Authority.
5) Aggregation of required data for CCG and Local Authority management use will be completed by Optum health Solutions (UK) Ltd or the CCG/Local Authority as instructed by the CCG.
6) Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority 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 the NHS Digital guidance applicable to each data set.
7) Optum Health Solutions (UK) Ltd will only be in receipt of data specified in Point 1 and only be permitted to act as Data Processors for the period specified in the NHS England contract with NHS Oxfordshire CCG.
Data Processor 3 – NHS Berkshire West CCG
1) Pseudonymised SUS data is securely transferred from the DSCRO to NHS Berkshire West CCG.
2) The DSCRO will receive and process Local Provider data for the London providers and disseminate the pseudonymised data to NHS Berkshire West CCG via the NEL / NOE / SCW CSU.
3) Data will be pseudonymised in such a way as to allow linkage between data in points (1) and (2) above.
4) NHS Berkshire West CCG add derived fields, link SUS fields and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning (CCG).
o Check recorded activity against contracts or invoices and facilitate discussions with providers (CCG).
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
5) NHS Berkshire West CCG then pass the processed, pseudonymised and linked data to the CCG and Local Authority.
6) Aggregation of required data for CCG and Local Authority management use will be completed by NHS Berkshire West CCG or the CCG/Local Authority as instructed by the CCG.
7) Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority 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 - University of Oxford - Medical Sciences Division - Nuffield Department of Primary Care Health Sciences: SCAN Pathway evaluation project
1) Pseudonymised SUS+, CWT, DIDs, Local Provider data flows and GP Primary Care Data is securely transferred from NHS Oxfordshire CCG (or NHS SCW CSU) to the Nuffield Department of Primary Care Health Sciences at University of Oxford.
2) Nuffield Department of Primary Care Health Sciences provide analysis to:
o Create a comparator data cohort to the SCAN pathway
o Analyse the net efficacy of the SCAN pathway in Oxfordshire
o Analyse and evaluate the SCAN pathway
o Analytics to assist with pathway redesign
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
3) Allowed linkage is between the datasets contained in point 1 above. No further linkage is permitted.
4) Aggregation of required data for CCG and Local Authority management use will be completed by the Nuffield Department of Primary Care Health Sciences at University of Oxford or the CCG/Local Authority as instructed by the CCG
5) Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority 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.
Pilot Programme
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) data, Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data), GP data and Social Care data is transferred from South Central and West Commissioning Support Unit to;
• Oxford University Hospitals NHS Foundation Trust
• Oxford Health NHS Foundation Trust
• South Central Ambulance Services NHS Foundation Trust
2. The 3 organisations listed above will process and analyse the data under data processing contracts with the CCG.
3. Data received by the processors will be held separately from identifiable data they hold so cannot be linked. The Local Patient ID field will not be included in the dataset.
4. The 3 data processors then pass the processed data back to the CCG and Local Authority.
5. Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority 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 the NHS Digital guidance applicable to each data set.
Expected output
Commissioning
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
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
Pilot Programme
• Reports analysing patient pathways across multiple NHS services
• Improvement plans developed to address identified opportunities
Expected measurable benefits
COMMISSIONING
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.
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
Pilot Programme
• Monitoring of patients across services to understand the full patient pathway and interdependency of care
• Redesign of service to improve efficiencies and patient experiences
• Allow a more joined up approach to care to support the future Integrated Care System approach to care
• Target care more effectively
Benefits reported so far
The following yielded benefits have been realised through the processing/support of NHS Digital data:
Improving diabetes care and prevention- A multi-organisational team including clinicians and managers from the CCG, Oxford University Health Trust, Oxford Health and the South Central & West Commissioning Support Unit, developed a Diabetes Dashboard, which presents diabetes care and health outcomes data monthly for the Oxfordshire diabetes population. It presents data at county, PCN and GP practice level, thereby providing regular insight into Oxfordshire diabetes population health. The Dashboard has subsequently been used in regular visits in GP practices and PCNs by Diabetes Consultants and Community Diabetes Specialist Nurses to develop supportive multi-disciplinary working and joined up care across primary, community and secondary care that improves outcomes for people with diabetes. The implementation of the Dashboard and multi-disciplinary collaboration has played a significant role in improving the care of people with diabetes within Oxfordshire as is evidenced in the National Diabetes Audit (NDA).
The CCG has recently published their annual report for 2020/21 - https://www.oxfordshireccg.nhs.uk/get-involved/Annual%20Reports/OCCG%20Annual%20Report%20and%20Account%2020_21%20combined%20with%20signatures%2018_06_21%20final.pdf
A summary of the report can be found at https://www.oxfordshireccg.nhs.uk/get-involved/Annual%20Reports/OCCG%20Annual%20Report%20Summary%202020%20-2021.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.
Page 17 of the summary report describes;
Community Gynaecology Service
A new Community Gynaecology Service for Oxfordshire was set up to meet the growing demand for gynaecology care, to provide care closer to home and to reduce the number of unnecessary referrals to secondary care.
Many patients can be treated in the community, which protects the specialist hospital service and avoids unnecessary trips to hospitals – this has become even more important during the COVID-19 pandemic.
The community gynaecology service started with a pilot in Oxford City and North Oxfordshire in January 2020, with the service beginning expansion across the county in November 2020. The outcome of the pilot was that 50 per cent of patients were diverted from referral on to secondary care following triage by the community service.
The service is triaging all gynaecological referrals and continues to have good results.
Cancer services
Cancer services have been under significant pressure to deliver treatment for all patients.
OUH [Oxford University Hospitals] has been working with the Thames Valley Cancer Alliance (TVCA) on a recovery plan for cancer services to restore to at least pre-pandemic levels the number of people coming forward and appropriately being referred with suspected cancer.
In October 2020 OCCG started a pilot to trial C the Signs, a digital tool which uses artificial intelligence mapped with the latest evidence to identify patients at risk of cancer. 57 GP practices have signed up. Data is being collated and an evaluation will be made.
OCCG and OUH won Cancer Care Team of the Year at The British Medical Journal Awards 2020 for the innovative suspected cancer (SCAN) two-week pathway run at the Churchill Hospital in Oxford. The suspected cancer SCAN two-week pathway is specifically designed for patients with “low risk but not no risk” cancer symptoms to speed up diagnosis.
More than 2,513 patients have been scanned in the period up to 12 April 2021 from the service’s launch in 2018. A total of 216 patients have received a confirmed cancer diagnosis from the pathway and have gone on to receive the care they need.
Improving diabetes care and prevention
A multi-organisational team including clinicians and managers from OCCG, OUH, Oxford Health and the South Central and West Commissioning Support Unit, developed a Diabetes Dashboard, which presents monthly diabetes care and health outcomes data for Oxfordshire.
The Dashboard has been used to develop supportive, joined-up care across primary, community and secondary services, which improves outcomes for people with diabetes.
It has also been shortlisted for a prestigious Health Service Journal Value Award in the ‘Diabetes Care Initiative of the Year’ category.
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'
| Dataset | Type of data | Sensitivity | Frequency | Confidential data |
|---|---|---|---|---|
| Acute-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Adult Social Care | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Ambulance-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Children and Young People Health | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Civil Registration - Births | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Civil Registrations of Death | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Community Services Data Set (CSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Community-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Demand for Service-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Diagnostic Imaging Data Set (DID) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Diagnostic Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| e-Referral Service for Commissioning | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Emergency Care-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Experience, Quality and Outcomes-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Improving Access to Psychological Therapies (IAPT) v1.5 | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Maternity Services Data Set | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Medicines dispensed in Primary Care (NHSBSA data) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health and Learning Disabilities Data Set (MHLDDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health Minimum Data Set (MHMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health Services Data Set (MHSDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Mental Health-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| National Diabetes Audit | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Patient Reported Outcome Measures (PROMs) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Personal Demographic Service | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Population Data-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Primary Care Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Public Health and Screening Services-Local Provider Flows | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| Summary Hospital-level Mortality Indicator (SHMI) | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
| SUS for Commissioners | Anonymised - ICO Code Compliant | Sensitive | Frequent Adhoc Flow | Does not include the flow of confidential data |
Files released
Files released counts only files released externally by DARS. Access granted in NHS England's own systems, such as its Secure Data Environment, is not included.
No files recorded as released under this agreement.
Version history
The register lists each renewal of this agreement as a separate row. This site has 9 versions — earlier versions existed before this site's records begin.
DARS-NIC-116582-F2F2J-v11.4 17 June 2022 to 16 June 2025
- Title
- DSfC - NHS Oxfordshire CCG and Oxfordshire County Council; Comm.
- Commercial
- No
- Sublicensing
- No
- Datasets
- 31
- 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
What changed from DARS-NIC-116582-F2F2J-v10.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2022-06-17 | |
| End date | 2025-06-16 |
Datasets: + Adult Social Care
Objective for processing
[36 paragraphs unchanged]
- Adult Social Care data
[1 paragraph unchanged]
Processing of Adult Social Care data is only permitted for the Commissioning purposes set out within this agreement. Adult Social Care data will not be processed for the purpose of Risk Stratification.
[14 paragraphs unchanged]
-
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 South Central and West Commissioning Support Unit,
Atos Healthcare (part of Atos IT Services UK Limited), Optum Health Solutions (UK) Ltd, NHS North and East London CSU,
Oxfordshire University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust,
and
South Central Ambulance Services NHS Foundation
Trust.
Trust, and University of Oxford-Medical Sciences Division-Nuffield Department of Primary Care Health Services.
[1 paragraph unchanged]
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
Oxfordshire’s Suspected CANcer (SCAN) pathway evaluation
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
University of Oxford - Medical Sciences Division - Nuffield Department of Primary Care Health Sciences
Cancer is the leading cause of premature death in the UK and cancer patients have lower survival rates than comparable health economies. One explanation for the survival deficit is diagnostic delay. ‘Two-week-wait’ referral pathways were introduced to enable the urgent investigation of NHS patients with specific “red-flag” symptoms. As a consequence patients with Non-specific but Concerning Symptoms (NSCS) became ineligible for rapid investigation despite half of all cancer patients presenting with NSCS. These patients wait longer for referral and for a cancer diagnosis and are often diagnosed at a later stage when curative treatment is no longer an option. To address this problem, the Accelerate Coordinate Evaluate (ACE) programme was established to pilot rapid diagnostic pathways to detect cancer in patients with NSCS. This new ACE programme of work is funded by Cancer Research UK (CRUK) and National Health Service England (NHSE).
Ten NSCS pathways have been piloted in five NHS localities by Wave 2/second round of the ACE programme, and the Suspected CANcer (SCAN) pathway in Oxfordshire is one of them. Oxfordshire’s SCAN pathway is the only one to perform a CT scan first on all patients accepted for investigation.
NHS Oxfordshire CCG now wishes to evaluate the outcomes of patients referred to the SCAN pathway for investigation of a pre-specified set of symptoms compared to the outcomes of patients with the same symptoms investigated through existing routes to cancer diagnosis in Oxfordshire before and while the SCAN pathway was available. The results of the analysis will also help support the planned national rollout of similar vague symptoms pathways.
A comparator cohort dataset from SUS, CWT, Local Provider flows and GP data will be used to compare the SCAN cohort against, and to establish whether providing GPs with a dedicated pathway through which patients with low-risk but not no-risk symptoms can be investigated has reduced the time from initial primary care presentation to diagnosis, while matching or exceeding the diagnostic yield of pre-existing routes to cancer diagnosis for these patients.
[7 paragraphs unchanged]
The expectation is that this agreement will be superseded by the approval of anew Data Sharing Agreement (DSA) following the CCG's transition into an ICB. The appropriate data flows will be transferred to this new agreement.
Processing activities
[8 paragraphs unchanged]
An example of a request for the re-id of patients for direct care
may be;
are;
A&E High Attendance usage
· GPs have requested a list of patients registered with them who have depression, obesity, are on a waiting list, and aged 20-64. This is in order to assist them with direct patient care interventions for these patients to improve the outcomes using the existing services. The patient will benefit from an additional and more personalised support package and enhanced access to support. Any lessons learnt will also enable them to make changes to strengthen the patient pathway to others with the same conditions.
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.
· GPs have requested a list of patients registered with them who are adolescents between the age of 15 – 24 who are asthmatic and have a mental health diagnosis. This is in order to assist them with direct patient care interventions for these patients to improve the outcomes using the existing services. The patient will benefit from an additional and more personalised support package and enhanced access to support. Any lessons learnt will also enable them to make changes to strengthen the patient pathway to others with the same conditions.
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.
[1 paragraph unchanged]
1. The CCG identifies a patient cohort
(typically small numbers)
to be re-identified for the purpose of direct care.
Consideration of identifying the patient cohort will be two-fold, from both a clinical commissioning perspective and a data led perspective. The process will be followed on a programmatic basis or, rarely, individual / small cohorts.
[1 paragraph unchanged]
3. The DSCRO
(either through an automated system or manual checking in line with the request)
assesses as to whether the request passes the specified re-identification process checks.
[35 words unchanged]
for example around timings and the requestor’s relationship with patients in the
data
data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system.
4. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
4. For automated systems, steps 1 - 3 wouldn’t apply in most cases as it would be the direct care professional who identifies the cohort and as long as they are an approved re-id user and have gone through security checks initially, they will be able to re-id without further checks.
5. DSCROs retain an audit trail of all re-id requests
5. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or Care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
6. National Data opt outs are not applied for the purpose of direct care
6. DSCROs retain an audit trail of all re-id requests
[14 paragraphs unchanged]
• Patients treated by a provider where NHS Oxfordshire CCG has joint responsibility for the provider services in the local health economy – this is only for Ambulance Trust data
and/or
[4 paragraphs unchanged]
Microsoft Limited
supply
provide
Cloud
services to
Services for NHS North of England Commissioning Support Unit, North East London Commissioning Support Unit,
Optum Health Solutions UK
Ltd, SCW CSU,
Limited
and
NEL CSU
South Central and West Commissioning Support Unit
and are therefore listed as a data processor. They supply support to
[24 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
Amazon Web Services
supply
provide
Cloud
services to
Services for
Optum Health Solutions UK Limited and are therefore listed as a data
[29 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
Pulsant, IT Professional Services Ltd, Interxion, Ark Data Centres and
University Hospitals Bristol NHS Foundation Trust do not access data held under
[25 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
Interxion and Ark Data Centres do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
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
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.
[32 paragraphs unchanged]
19.Medicines
19. Medicines
Dispensed in Primary Care (NHSBSA Data)
20. Adult Social Care data
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[50 words unchanged]
e-Referral Service (eRS) data, 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 held within the DSCRO until the completion of points 2-8.
[23 paragraphs unchanged]
4. Once the pseudonymised GP
data
and social care data is received, the CSU make a request to the DSCRO.
5. The DSCRO checks the dates of the key generation (Point 2e
and
&
3e/3b).
[13 paragraphs unchanged]
12. Allowed linkage is between the data sets contained within point 1, point 2 and point
3.
3 and point 4.
No further linkage is permitted.
[3 paragraphs unchanged]
Atos Healthcare (part of Atos IT services UK Limited)
Data Processor 2 - Optum Health Solutions (UK) Ltd - for the NHS England second round/Wave 2 PHM project
Atos Healthcare (part of Atos IT services UK Limited) will be providing South Central and West Commissioning Support Unit with staff resource and subject matter expertise to assist in the delivery of products and services. Named individuals will have access to pseudonymised patient level data via South Central and West Commissioning Support Unit servers and secure logins. No data will leave South Central and West Commissioning Support Unit, therefore no processing and storage addresses are listed.
Data Processor 2 – Optum Health Solutions (UK) Ltd
1) Pseudonymised SUS data is securely transferred from SCW DSCRO to Optum Health Solutions (UK) Ltd.
2) NEL DSCRO will receive and process Local Provider data for the London providers and disseminate the pseudonymised data to Optum Health Solutions (UK) Ltd via the NEL CSU SFTP process.
3) Data will be pseudonymised in such a way as to allow linkage between data in points (1) and (2) above.
4) Optum Health Solutions (UK) Ltd add derived fields, link SUS fields and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning (CCG).
o Check recorded activity against contracts or invoices and facilitate discussions with providers (CCG).
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
5) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG and Local Authority.
6) Aggregation of required data for CCG and Local Authority management use will be completed by Optum Health Solutions (UK) Ltd or the CCG/Local Authority as instructed by the CCG.
7) Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
Data Processor 3 - Optum Health Solutions (UK) Ltd - for the NHS England Wave 2 PHM project
[12 paragraphs unchanged]
Data held by Optum Health Solutions (UK) Ltd for the purpose of the NHS England Wave 2 PHM project will be destroyed within 6 months of the completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Data Processor 3 – NHS Berkshire West CCG
1) Pseudonymised SUS data is securely transferred from the DSCRO to NHS Berkshire West CCG.
2) The DSCRO will receive and process Local Provider data for the London providers and disseminate the pseudonymised data to NHS Berkshire West CCG via the NEL / NOE / SCW CSU.
3) Data will be pseudonymised in such a way as to allow linkage between data in points (1) and (2) above.
4) NHS Berkshire West CCG add derived fields, link SUS fields and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning (CCG).
o Check recorded activity against contracts or invoices and facilitate discussions with providers (CCG).
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
5) NHS Berkshire West CCG then pass the processed, pseudonymised and linked data to the CCG and Local Authority.
6) Aggregation of required data for CCG and Local Authority management use will be completed by NHS Berkshire West CCG or the CCG/Local Authority as instructed by the CCG.
7) Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority 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 - University of Oxford - Medical Sciences Division - Nuffield Department of Primary Care Health Sciences: SCAN Pathway evaluation project
1) Pseudonymised SUS+, CWT, DIDs, Local Provider data flows and GP Primary Care Data is securely transferred from NHS Oxfordshire CCG (or NHS SCW CSU) to the Nuffield Department of Primary Care Health Sciences at University of Oxford.
2) Nuffield Department of Primary Care Health Sciences provide analysis to:
o Create a comparator data cohort to the SCAN pathway
o Analyse the net efficacy of the SCAN pathway in Oxfordshire
o Analyse and evaluate the SCAN pathway
o Analytics to assist with pathway redesign
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
3) Allowed linkage is between the datasets contained in point 1 above. No further linkage is permitted.
4) Aggregation of required data for CCG and Local Authority management use will be completed by the Nuffield Department of Primary Care Health Sciences at University of Oxford or the CCG/Local Authority as instructed by the CCG
5) Patient level data will not be shared outside of the CCG and Local Authority and will only be shared within the CCG and Local Authority 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.
[9 paragraphs unchanged]
Expected output
[47 paragraphs unchanged]
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
26. Identify medication prescribing trends and their effectiveness.
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
27. Linking prescribing habits to entry points into the health and social care system
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
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
[3 paragraphs unchanged]
Expected measurable benefits
[43 paragraphs unchanged] 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 [5 paragraphs unchanged]
Benefits reported
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
The following yielded benefits have been realised through the processing/support of NHS Digital data:
Listed below is a number of further yielded benefits for commissioning;
Improving diabetes care and prevention- A multi-organisational team including clinicians and managers from the CCG, Oxford University Health Trust, Oxford Health and the South Central & West Commissioning Support Unit, developed a Diabetes Dashboard, which presents diabetes care and health outcomes data monthly for the Oxfordshire diabetes population. It presents data at county, PCN and GP practice level, thereby providing regular insight into Oxfordshire diabetes population health. The Dashboard has subsequently been used in regular visits in GP practices and PCNs by Diabetes Consultants and Community Diabetes Specialist Nurses to develop supportive multi-disciplinary working and joined up care across primary, community and secondary care that improves outcomes for people with diabetes. The implementation of the Dashboard and multi-disciplinary collaboration has played a significant role in improving the care of people with diabetes within Oxfordshire as is evidenced in the National Diabetes Audit (NDA).
1. Monitoring In year projects
The CCG has recently published their annual report for 2020/21 - https://www.oxfordshireccg.nhs.uk/get-involved/Annual%20Reports/OCCG%20Annual%20Report%20and%20Account%2020_21%20combined%20with%20signatures%2018_06_21%20final.pdf
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
A summary of the report can be found at https://www.oxfordshireccg.nhs.uk/get-involved/Annual%20Reports/OCCG%20Annual%20Report%20Summary%202020%20-2021.pdf
3. Successful delivery of integrated care within the CCG.
This report highlights the achievements made during the year, of which some would only have been achieved by using the data from NHS Digital.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
Page 17 of the summary report describes;
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
Community Gynaecology Service
The CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
A new Community Gynaecology Service for Oxfordshire was set up to meet the growing demand for gynaecology care, to provide care closer to home and to reduce the number of unnecessary referrals to secondary care.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
Many patients can be treated in the community, which protects the specialist hospital service and avoids unnecessary trips to hospitals – this has become even more important during the COVID-19 pandemic.
The community gynaecology service started with a pilot in Oxford City and North Oxfordshire in January 2020, with the service beginning expansion across the county in November 2020. The outcome of the pilot was that 50 per cent of patients were diverted from referral on to secondary care following triage by the community service.
The service is triaging all gynaecological referrals and continues to have good results.
Cancer services
Cancer services have been under significant pressure to deliver treatment for all patients.
OUH [Oxford University Hospitals] has been working with the Thames Valley Cancer Alliance (TVCA) on a recovery plan for cancer services to restore to at least pre-pandemic levels the number of people coming forward and appropriately being referred with suspected cancer.
In October 2020 OCCG started a pilot to trial C the Signs, a digital tool which uses artificial intelligence mapped with the latest evidence to identify patients at risk of cancer. 57 GP practices have signed up. Data is being collated and an evaluation will be made.
OCCG and OUH won Cancer Care Team of the Year at The British Medical Journal Awards 2020 for the innovative suspected cancer (SCAN) two-week pathway run at the Churchill Hospital in Oxford. The suspected cancer SCAN two-week pathway is specifically designed for patients with “low risk but not no risk” cancer symptoms to speed up diagnosis.
More than 2,513 patients have been scanned in the period up to 12 April 2021 from the service’s launch in 2018. A total of 216 patients have received a confirmed cancer diagnosis from the pathway and have gone on to receive the care they need.
Improving diabetes care and prevention
A multi-organisational team including clinicians and managers from OCCG, OUH, Oxford Health and the South Central and West Commissioning Support Unit, developed a Diabetes Dashboard, which presents monthly diabetes care and health outcomes data for Oxfordshire.
The Dashboard has been used to develop supportive, joined-up care across primary, community and secondary services, which improves outcomes for people with diabetes.
It has also been shortlisted for a prestigious Health Service Journal Value Award in the ‘Diabetes Care Initiative of the Year’ category.
Further information about other achievements and future priorities can be found within the report.
DARS-NIC-116582-F2F2J-v10.3 18 March 2021 to 17 March 2024
- Title
- DSfC - NHS Oxfordshire CCG and Oxfordshire County Council; Comm.
- Commercial
- No
- Sublicensing
- No
- Datasets
- 30
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; 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
What changed from DARS-NIC-116582-F2F2J-v9.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Title | DSfC - NHS Oxfordshire CCG and Oxfordshire County Council; Comm. | |
| Data controller basis | Joint Data Controller | |
| Start date | 2021-03-18 | |
| End date | 2024-03-17 | |
| Acute-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Ambulance-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Children and Young People Health: common law duty of confidentiality | Does not include the flow of confidential data | |
| Civil Registration - Births: common law duty of confidentiality | Does not include the flow of confidential data | |
| Civil Registrations of Death: common law duty of confidentiality | Does not include the flow of confidential data | |
| Community Services Data Set (CSDS): common law duty of confidentiality | Does not include the flow of confidential data | |
| Community-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Demand for Service-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Diagnostic Imaging Data Set (DID): common law duty of confidentiality | Does not include the flow of confidential data | |
| Diagnostic Services-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Emergency Care-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Experience, Quality and Outcomes-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Improving Access to Psychological Therapies Data Set_v1.5: common law duty of confidentiality | Does not include the flow of confidential data | |
| Maternity Services Data Set v1.5: common law duty of confidentiality | Does not include the flow of confidential data | |
| Mental Health Minimum Data Set (MHMDS): common law duty of confidentiality | Does not include the flow of confidential data | |
| Mental Health Services Data Set (MHSDS): common law duty of confidentiality | Does not include the flow of confidential data | |
| Mental Health and Learning Disabilities Data Set (MHLDDS): common law duty of confidentiality | Does not include the flow of confidential data | |
| Mental Health-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS): common law duty of confidentiality | Does not include the flow of confidential data | |
| National Diabetes Audit: common law duty of confidentiality | Does not include the flow of confidential data | |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Patient Reported Outcome Measures (PROMs): common law duty of confidentiality | Does not include the flow of confidential data | |
| Personal Demographic Service: common law duty of confidentiality | Does not include the flow of confidential data | |
| Population Data-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Primary Care Services-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| Public Health and Screening Services-Local Provider Flows: common law duty of confidentiality | Does not include the flow of confidential data | |
| SUS for Commissioners: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| SUS for Commissioners: type of data | Anonymised - ICO Code Compliant | |
| SUS for Commissioners: common law duty of confidentiality | Does not include the flow of confidential data | |
| Summary Hospital-level Mortality Indicator (SHMI): common law duty of confidentiality | Does not include the flow of confidential data | |
| e-Referral Service for Commissioning: common law duty of confidentiality | Does not include the flow of confidential data |
Data controllers: + OXFORDSHIRE COUNTY COUNCIL
Datasets: + Medicines dispensed in Primary Care (NHSBSA data)
Objective for processing
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (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 NHS South, Central and West Commissioning Support Unit
[1 paragraph unchanged]
To use pseudonymised data to provide intelligence to support the commissioning of
[17 words unchanged]
can be planned to support the needs of the population within the
CCG
Oxfordshire
area.
The
CCGs
Clinical Commissioning Group (CCG) and Local Authority
commission services from a range of providers covering a wide array of
[5 words unchanged]
flow categories requested supports the commissioned activity of one or more providers.
The CCG and Local Authority are also part of a programme that focuses on population health management that aims to improve healthcare of the local population through focusing on specific activities.
The CCG and Council are setting up a Joint Commissioning team, where most of the team will be employed by the Council but will obviously need access to the same health data as CCG colleagues to enable the whole team to fulfil their Commissioning team functions. This is also in preparation for being part of the same Integrated Care System.
[31 paragraphs unchanged]
- Medicines Dispensed in Primary Care (NHSBSA Data)
Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.
[4 paragraphs unchanged]
o Using value as the redesign principle
[10 paragraphs unchanged]
Provide intelligence about the safety and effectiveness of medicines.
[1 paragraph unchanged]
Processing for commissioning will be conducted by South Central and West Commissioning
[21 words unchanged]
CSU, Oxfordshire University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust,
and
South Central Ambulance Services NHS Foundation
Trust, and Oxfordshire County Council.
Trust.
Each of the Data Processors specified above has a distinct set task, and there is no duplication of effort.
[3 paragraphs unchanged]
Due to increasing demand on services, the CCG is constantly attempting to
[84 words unchanged]
Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust)
and 1 Local Authority (Oxfordshire County Council)
as data processors.
[5 paragraphs unchanged]
Processing activities
[6 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.
(RS) 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.
[1 paragraph 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
[5 paragraphs unchanged]
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.
[8 paragraphs unchanged]
For the purpose of Risk Stratification:
and/or
• Patients who are normally registered and/or resident within NHS Oxfordshire CCG (including historical activity where the patient was previously registered or resident in another commissioner
• The population for which Oxfordshire County Council has responsibility for.
For the purpose of Invoice Validation:
• Patients who are resident and/or registered within the CCG region.
[3 paragraphs unchanged]
Microsoft Limited supply Cloud services to Optum Health Solutions UK Ltd,
Liaison Financial services,
SCW CSU, and NEL CSU and are therefore listed as a data
[29 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[4 paragraphs unchanged]
INVOICE VALIDATION - South Central and West Commissioning Support Unit
1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the NHS South, Central and West Commissioning Support Unit.
3. The CEfF also receive backing data from the provider.
4. NHS South, Central and West Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes:
a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.
b. Once the provider backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between NHS South, Central and West Commissioning Support Unit CEfF team and the provider, meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.
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
1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to NHS South, Central and West Commissioning Support Unit, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to NHS South, Central and West Commissioning Support Unit.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once NHS South, Central and West Commissioning Support Unit has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level
[32 paragraphs unchanged]
19.Medicines Dispensed in Primary Care (NHSBSA Data)
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[45 words unchanged]
Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS) data, Personal Demographics Service
(PDS) and
(PDS),
Summary Hospital-level Mortality Indicator (SHMI)
and Medicines Dispensed in Primary Care (NHSBSA Data)
data only is held within the DSCRO until the completion of points 2-8.
[39 paragraphs unchanged]
13. NHS South, Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the
CCG.
CCG and Local Authority
14. Aggregation of required data for CCG
and Local Authority
management use will be completed by NHS South, Central and West Commissioning Support Unit or the
CCG
CCG/Local Authority
as instructed by the
CCG.
CCG/Local Authority.
15. Patient level data will not be shared outside of the CCG and
Local Authority and
will only be shared within the CCG
and Local Authority
on a need to know basis, as per the purposes stipulated within
[15 words unchanged]
as set out within NHS Digital guidance applicable to each data set.
[14 paragraphs unchanged]
5) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the
CCG.
CCG and Local Authority.
6) Aggregation of required data for CCG
and Local Authority
management use will be completed by Optum Health Solutions (UK) Ltd or the
CCG
CCG/Local Authority
as instructed by the CCG.
7) Patient level data will not be shared outside of the CCG and
Local Authority and
will only be shared within the CCG
and Local Authority
on a need to know basis, as per the purposes stipulated within
[15 words unchanged]
as set out within NHS Digital guidance applicable to each data set.
[9 paragraphs unchanged]
4) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the
CCG.
CCG and Local Authority.
5) Aggregation of required data for CCG
and Local Authority
management use will be completed by Optum health Solutions (UK) Ltd or the
CCG
CCG/Local Authority
as instructed by the CCG.
6) Patient level data will not be shared outside of the CCG and
Local Authority and
will only be shared within the CCG
and Local Authority
on a need to know basis, as per the purposes stipulated within
[16 words unchanged]
set out within the NHS Digital guidance applicable to each data set.
[3 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[51 words unchanged]
Service (eRS) data, Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI),
Medicines Dispensed in Primary Care (NHSBSA Data),
GP data and Social Care data is transferred from South Central and West Commissioning Support Unit to;
[3 paragraphs unchanged]
• Oxfordshire County Council
2. The 3 organisations listed above will process and analyse the data under data processing contracts with the CCG.
2. The 4 organisations listed above will process and analyse the data under data processing contracts with the CCG.
[1 paragraph unchanged]
4. The
4
3
data processors then pass the processed data back to the CCG
and Local Authority.
5. Patient level data will not be shared outside of the CCG and
Local Authority and
will only be shared within the CCG
and Local Authority
on a need to know basis, as per the purposes stipulated within
[16 words unchanged]
set out within the NHS Digital guidance applicable to each data set.
Expected output
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.
[53 paragraphs unchanged]
Expected measurable benefits
INVOICE VALIDATION
The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by:
1. Ensuring that activity is fully financially validated.
2. Ensuring that service providers are accurately paid for the patients treatment.
3. Enabling services to be planned, commissioned, managed, and subjected to financial control.
4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they are responsible.
5. Fulfilling commissioners duties to fiscal probity and scrutiny.
6. Ensuring full financial accountability for relevant organisations.
7. Ensuring robust commissioning and performance management.
8. Ensuring commissioning objectives do not compromise patient confidentiality.
9. Ensuring the avoidance of misappropriation of public funds.
INVOICE VALIDATION – Liaison Financial Services Ltd
1. Financial validation of activity
2. CCG Budget control
3. Assurances over the robustness of internal control mechanisms relating to the payment of invoices and/or suggested improvements
4. Identification and recovery of monies which would otherwise be lost
5. Meeting commissioning objectives without compromising patient confidentiality
6. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
7. Benefit delivered 3-9 months from receiving data, depending on number of claims to investigate and resolve
RISK STRATIFICATION
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early intervention.
3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care.
5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes
All of the above lead to improved patient experience through more effective commissioning of services.
[48 paragraphs unchanged]
Benefits reported
Learned from and predicted likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
The CCG now has a better understanding of the health of and variations in health outcomes within the population it serves
Listed below is a number of further yielded benefits for commissioning;
The CCG has a better understanding of contract requirements, contract execution and required services for management of existing contracts
1. Monitoring In year projects
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
3. Successful delivery of integrated care within the CCG.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
The CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
Objective for processing
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 Oxfordshire area.
The Clinical Commissioning Group (CCG) and Local Authority 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 CCG and Local Authority are also part of a programme that focuses on population health management that aims to improve healthcare of the local population through focusing on specific activities.
The CCG and Council are setting up a Joint Commissioning team, where most of the team will be employed by the Council but will obviously need access to the same health data as CCG colleagues to enable the whole team to fulfil their Commissioning team functions. This is also in preparation for being part of the same Integrated Care System.
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)
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:
o Understanding the interdependency of care services
o Targeting care more effectively
- Data Quality and Validation – allowing data quality checks on the submitted data
- Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
- Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
- Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
- Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
- Service redesign
- Health Needs Assessment – identification of underlying disease prevalence within the local population
- Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
- Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
- Support measuring the health, mortality or care needs of the total local population
Provide intelligence about the safety and effectiveness of medicines.
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 South Central and West Commissioning Support Unit, Atos Healthcare (part of Atos IT Services UK Limited), Optum Health Solutions (UK) Ltd, NHS North and East London CSU, Oxfordshire University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, and South Central Ambulance Services NHS Foundation Trust.
Each of the Data Processors specified above has a distinct set task, and there is no duplication of effort.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Pilot Programme
Due to increasing demand on services, the CCG is constantly attempting to find new ways to improve the services that it commissions. One of the key issues is that patient pathways can span multiple secondary care services, each operated by different secondary care organisations. The NHS England 5 year forward plan is an attempt to tackle this complication by encouraging a more joined up approach to a patient’s care. In order to deliver on this in the current NHS structure, the CCG has proposed to engage 3 NHS Foundations Trusts (Oxford University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust) as data processors.
They will be given access to the pseudonymised data in order to:
• analyse and investigate patients across pathways of care
• to identify healthcare consumption and capacity issues
• understand the interdependency of care services
• look at demand management and service redesign.
Expected output
Commissioning
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
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
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Pilot Programme
• Reports analysing patient pathways across multiple NHS services
• Improvement plans developed to address identified opportunities
Benefits reported
The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.
Listed below is a number of further yielded benefits for commissioning;
1. Monitoring In year projects
2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
3. Successful delivery of integrated care within the CCG.
4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
The CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.
Benefits to date are in line with what the CCG expected to achieve at the point in time as described in the previous application. The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.
DARS-NIC-116582-F2F2J-v9.2 15 October 2020 to 14 October 2023
- Title
- DSfC - NHS Oxfordshire CCG; RS, IV, Comm.
- Commercial
- No
- Sublicensing
- No
- Datasets
- 30
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Personal Demographic Service; Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; Summary Hospital-level Mortality Indicator (SHMI); SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-116582-F2F2J-v8.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
Objective for processing
[60 paragraphs unchanged]
Processing for commissioning will be conducted by South Central and West Commissioning Support Unit, Atos Healthcare (part of Atos IT Services UK Limited), Optum Health Solutions (UK)
Ltd &
Ltd,
NHS North and East London
CSU.
CSU, Oxfordshire University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust, and Oxfordshire County Council.
[2 paragraphs unchanged]
Pilot Programme
Due to increasing demand on services, the CCG is constantly attempting to find new ways to improve the services that it commissions. One of the key issues is that patient pathways can span multiple secondary care services, each operated by different secondary care organisations. The NHS England 5 year forward plan is an attempt to tackle this complication by encouraging a more joined up approach to a patient’s care. In order to deliver on this in the current NHS structure, the CCG has proposed to engage 3 NHS Foundations Trusts (Oxford University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust) and 1 Local Authority (Oxfordshire County Council) as data processors.
They will be given access to the pseudonymised data in order to:
• analyse and investigate patients across pathways of care
• to identify healthcare consumption and capacity issues
• understand the interdependency of care services
• look at demand management and service redesign.
Processing activities
[32 paragraphs unchanged]
Microsoft Limited supply Cloud services to Optum Health Solutions UK Ltd, Liaison Financial services, SCW
CSU
CSU,
and NEL CSU and are therefore listed as a data processor. They
[27 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[141 paragraphs unchanged]
Pilot Programme
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) data, Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), GP data and Social Care data is transferred from South Central and West Commissioning Support Unit to;
• Oxford University Hospitals NHS Foundation Trust
• Oxford Health NHS Foundation Trust
• South Central Ambulance Services NHS Foundation Trust
• Oxfordshire County Council
2. The 4 organisations listed above will process and analyse the data under data processing contracts with the CCG.
3. Data received by the processors will be held separately from identifiable data they hold so cannot be linked. The Local Patient ID field will not be included in the dataset.
4. The 4 data processors then pass the processed data back to the CCG
5. 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 the NHS Digital guidance applicable to each data set.
Expected output
[78 paragraphs unchanged] Pilot Programme • Reports analysing patient pathways across multiple NHS services • Improvement plans developed to address identified opportunities
Expected measurable benefits
[70 paragraphs unchanged] Pilot Programme • Monitoring of patients across services to understand the full patient pathway and interdependency of care • Redesign of service to improve efficiencies and patient experiences • Allow a more joined up approach to care to support the future Integrated Care System approach to care • Target care more effectively
Benefits reported
Not stated in the previous version; added here.
Learned from and predicted likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
The CCG now has a better understanding of the health of and variations in health outcomes within the population it serves
The CCG has a better understanding of contract requirements, contract execution and required services for management of existing contracts
Objective for processing
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (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 NHS South, Central and West Commissioning Support Unit
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
The pseudonymised data is required to for the following purposes:
- Population health management:
o Understanding the interdependency of care services
o Targeting care more effectively
o Using value as the redesign principle
- Data Quality and Validation – allowing data quality checks on the submitted data
- Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
- Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
- Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
- Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
- Service redesign
- Health Needs Assessment – identification of underlying disease prevalence within the local population
- Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
- Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
- Support measuring the health, mortality or care needs of the total local population
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by South Central and West Commissioning Support Unit, Atos Healthcare (part of Atos IT Services UK Limited), Optum Health Solutions (UK) Ltd, NHS North and East London CSU, Oxfordshire University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust, and Oxfordshire County Council.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Pilot Programme
Due to increasing demand on services, the CCG is constantly attempting to find new ways to improve the services that it commissions. One of the key issues is that patient pathways can span multiple secondary care services, each operated by different secondary care organisations. The NHS England 5 year forward plan is an attempt to tackle this complication by encouraging a more joined up approach to a patient’s care. In order to deliver on this in the current NHS structure, the CCG has proposed to engage 3 NHS Foundations Trusts (Oxford University Hospitals NHS Foundation Trust, Oxford Health NHS Foundation Trust, South Central Ambulance Services NHS Foundation Trust) and 1 Local Authority (Oxfordshire County Council) as data processors.
They will be given access to the pseudonymised data in order to:
• analyse and investigate patients across pathways of care
• to identify healthcare consumption and capacity issues
• understand the interdependency of care services
• look at demand management and service redesign.
Expected output
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 patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
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
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Pilot Programme
• Reports analysing patient pathways across multiple NHS services
• Improvement plans developed to address identified opportunities
Benefits reported
Learned from and predicted likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
The CCG now has a better understanding of the health of and variations in health outcomes within the population it serves
The CCG has a better understanding of contract requirements, contract execution and required services for management of existing contracts
DARS-NIC-116582-F2F2J-v8.3 15 October 2020 to 14 October 2023
- Title
- DSfC - NHS Oxfordshire CCG; RS, IV, Comm.
- Commercial
- No
- Sublicensing
- No
- Datasets
- 30
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Personal Demographic Service; Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; Summary Hospital-level Mortality Indicator (SHMI); SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-116582-F2F2J-v7.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-10-15 | |
| End date | 2023-10-14 | |
| Acute-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Ambulance-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Children and Young People Health: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registration - Births: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Civil Registrations of Death: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community Services Data Set (CSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Community-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Demand for Service-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Imaging Data Set (DID): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Diagnostic Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Emergency Care-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Experience, Quality and Outcomes-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Improving Access to Psychological Therapies Data Set_v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Maternity Services Data Set v1.5: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Minimum Data Set (MHMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health Services Data Set (MHSDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health and Learning Disabilities Data Set (MHLDDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Mental Health-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Cancer Waiting Times Monitoring DataSet (NCWTMDS): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| National Diabetes Audit: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Other Not Elsewhere Classified (NEC)-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Patient Reported Outcome Measures (PROMs): legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Population Data-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Primary Care Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| Public Health and Screening Services-Local Provider Flows: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' | |
| SUS for Commissioners: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'. | |
| e-Referral Service for Commissioning: legal basis | Health and Social Care Act 2012 - s261 - 'Other dissemination of information' |
Datasets: + Personal Demographic Service; + Summary Hospital-level Mortality Indicator (SHMI)
Objective for processing
[42 paragraphs unchanged] - Personal Demographics Service (PDS) - Summary Hospital-level Mortality Indicator (SHMI) [12 paragraphs unchanged] - Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such [7 words unchanged] executed against linked de-identified data, and identification of future service delivery models [1 paragraph unchanged] - Support measuring the health, mortality or care needs of the total local population [4 paragraphs unchanged]
Processing activities
[32 paragraphs unchanged]
Microsoft Limited supply Cloud services to
Optum Health Solutions UK Ltd,
Liaison Financial services, SCW CSU and NEL CSU and are therefore listed
[32 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
Amazon Web Services supply Cloud services to Optum Health Solutions UK Limited and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
[62 paragraphs unchanged]
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[32 words unchanged]
Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit
(NDA) and
(NDA),
Patient Reported Outcome Measures
(PROMs) and
(PROMs),
e-Referral Service (eRS)
data, Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI)
data only is held within the DSCRO until the completion of points 2-8.
[73 paragraphs unchanged]
Expected output
[71 paragraphs unchanged] 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 [3 paragraphs unchanged]
Expected measurable benefits
[62 paragraphs unchanged]
19. Assists commissioners to make better decisions to support patients
and drive changes in health care
20. Help drive changes in healthcare
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. 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. Inform commissioners and improve services
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. 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.
23. Monitoring of entire population, as a pose to only those that engage with services
24. Understanding the interdependency of care 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. Targeting care more effectively
25. Monitor the quality and safety of the delivery of healthcare services.
26. Using value as the redesign principle
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
27. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
28. Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
29. Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
30. Service redesign
31. Health Needs Assessment – identification of underlying disease prevalence within the local population
32. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
Objective for processing
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (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 NHS South, Central and West Commissioning Support Unit
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
The pseudonymised data is required to for the following purposes:
- Population health management:
o Understanding the interdependency of care services
o Targeting care more effectively
o Using value as the redesign principle
- Data Quality and Validation – allowing data quality checks on the submitted data
- Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
- Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
- Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
- Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
- Service redesign
- Health Needs Assessment – identification of underlying disease prevalence within the local population
- Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
- Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
- Support measuring the health, mortality or care needs of the total local population
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by South Central and West Commissioning Support Unit, Atos Healthcare (part of Atos IT Services UK Limited), Optum Health Solutions (UK) Ltd & NHS North and East London CSU.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Expected output
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 patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
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
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
DARS-NIC-116582-F2F2J-v7.2 12 August 2020 to 11 August 2023
- Title
- DSfC - NHS Oxfordshire CCG; RS, IV, Comm.
- Commercial
- No
- Sublicensing
- No
- Datasets
- 28
- Files released
- 0
Datasets: Acute-Local Provider Flows; Ambulance-Local Provider Flows; Children and Young People Health; Civil Registration - Births; Civil Registrations of Death; Community Services Data Set (CSDS); Community-Local Provider Flows; Demand for Service-Local Provider Flows; Diagnostic Imaging Data Set (DID); Diagnostic Services-Local Provider Flows; e-Referral Service for Commissioning; Emergency Care-Local Provider Flows; Experience, Quality and Outcomes-Local Provider Flows; Improving Access to Psychological Therapies (IAPT) v1.5; Maternity Services Data Set; Mental Health and Learning Disabilities Data Set (MHLDDS); Mental Health Minimum Data Set (MHMDS); Mental Health Services Data Set (MHSDS); Mental Health-Local Provider Flows; National Cancer Waiting Times Monitoring DataSet (NCWTMDS); National Diabetes Audit; Other Not Elsewhere Classified (NEC)-Local Provider Flows; Patient Reported Outcome Measures (PROMs); Population Data-Local Provider Flows; Primary Care Services-Local Provider Flows; Public Health and Screening Services-Local Provider Flows; SUS for Commissioners; SUS for Commissioners
What changed from DARS-NIC-116582-F2F2J-v6.1
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-08-12 | |
| End date | 2023-08-11 |
Datasets: + e-Referral Service for Commissioning
Objective for processing
[41 paragraphs unchanged]
- e-Referral Service (eRS)
[13 paragraphs unchanged]
- Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
[1 paragraph unchanged]
Processing for commissioning will be conducted by South Central and West Commissioning Support Unit,
Atos Healthcare (part of Atos IT Services UK Limited),
Optum Health Solutions (UK) Ltd & NHS North and East London CSU.
[1 paragraph unchanged]
NHS Oxfordshire CCG is working with NHS England as a Wave 2
[25 words unchanged]
to build up a methodology for dissemination across the NHS in England.
The NHS Oxfordshire CCG involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks.
Data held by Optum Health Solutions (UK) Ltd for this project will
[15 words unchanged]
processor for this project will be removed from this agreement by amendment.
Processing activities
[32 paragraphs unchanged]
Microsoft Limited supply Cloud services
to Liaison Financial services, SCW CSU and NEL CSU
and are therefore listed as a data processor. They supply support to
[24 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[2 paragraphs unchanged]
Invoice Validation
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.
INVOICE VALIDATION - South Central and West Commissioning Support Unit
[57 paragraphs unchanged]
16. e-Referral Service (eRS)
[2 paragraphs unchanged]
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[39 words unchanged]
and Deaths), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs)
and e-Referral Service (eRS) data
only is held within the DSCRO until the completion of points 2-8.
[42 paragraphs unchanged]
Atos Healthcare (part of Atos IT services UK Limited)
Atos Healthcare (part of Atos IT services UK Limited) will be providing South Central and West Commissioning Support Unit with staff resource and subject matter expertise to assist in the delivery of products and services. Named individuals will have access to pseudonymised patient level data via South Central and West Commissioning Support Unit servers and secure logins. No data will leave South Central and West Commissioning Support Unit, therefore no processing and storage addresses are listed.
[16 paragraphs unchanged]
1)
Pseudoymised
Pseudonymised
SUS+, Mental Health Services Data Set (MHSDS), Community Services Data Set (CSDS),
[28 words unchanged]
decoupled from the other national datasets and sent as individual data flows.
[11 paragraphs unchanged]
8) The NHS England / Optum contractual period with NHS Oxfordshire CCG is anticipated to end in July/August 2020, at which point the data processor permissions for this project will be removed from this agreement by amendment.
[1 paragraph unchanged]
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.
[47 paragraphs unchanged]
8. GP Practice level dashboard
reports include high flyers.
reports.
[5 paragraphs unchanged]
o
Most expensive patients
High cost activity uses
(top 15%)
[14 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.
[3 paragraphs unchanged]
Expected measurable benefits
[61 paragraphs unchanged] 18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 19. Assists commissioners to make better decisions to support patients 20. Help drive changes in healthcare 21. Allows comparisons of providers performance to assist improvement in services – increase the quality 22. Inform commissioners and improve services 23. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 24. Understanding the interdependency of care services 25. Targeting care more effectively 26. Using value as the redesign principle 27. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them 28. Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated 29. Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another 30. Service redesign 31. Health Needs Assessment – identification of underlying disease prevalence within the local population 32. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
Objective for processing
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (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 NHS South, Central and West Commissioning Support Unit
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
The pseudonymised data is required to for the following purposes:
- Population health management:
o Understanding the interdependency of care services
o Targeting care more effectively
o 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
- Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by South Central and West Commissioning Support Unit, Atos Healthcare (part of Atos IT Services UK Limited), Optum Health Solutions (UK) Ltd & NHS North and East London CSU.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Expected output
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 patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
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.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
DARS-NIC-116582-F2F2J-v6.1 1 June 2020 to 31 May 2023
- Title
- DSfC - NHS Oxfordshire CCG; RS, 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
What changed from DARS-NIC-116582-F2F2J-v5.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-06-01 | |
| End date | 2023-05-31 |
Objective for processing
[55 paragraphs unchanged]
Processing for commissioning will be conducted by South Central and West Commissioning Support
Unit &
Unit,
Optum Health Solutions (UK) Ltd
& NHS North and East London CSU.
[2 paragraphs unchanged]
Processing activities
[32 paragraphs unchanged]
Microsoft
UK
Limited
supply
IT infrastructure
Cloud services
and are therefore listed as a data processor. They supply support to
[24 words unchanged]
agreement. This includes granting of access to the database[s] containing the data.
[1 paragraph unchanged]
Interxion and Ark Data Centres do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
[104 paragraphs unchanged]
1) Pseudonymised
SUS+, and Local Provider
SUS
data
only
is securely transferred from
the
SCW
DSCRO to Optum Health Solutions (UK) Ltd.
2) Optum Health Solutions (UK) Ltd add derived fields, link SUS fields and provide analysis to:
2) NEL DSCRO will receive and process Local Provider data for the London providers and disseminate the pseudonymised data to Optum Health Solutions (UK) Ltd via the NEL CSU SFTP process.
3) Data will be pseudonymised in such a way as to allow linkage between data in points (1) and (2) above.
4) Optum Health Solutions (UK) Ltd add derived fields, link SUS fields and provide analysis to:
[7 paragraphs unchanged]
3) Allowed linkage is between the data sets contained within point 1.
5) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG.
4)
6) Aggregation of required data for CCG management use will be completed by
Optum Health Solutions (UK) Ltd
then pass
or
the
processed, pseudonymised and linked data to
CCG as instructed by
the CCG.
5) Aggregation of required data for CCG management use will be completed by Optum Health Solutions (UK) Ltd or the CCG as instructed by the CCG.
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.
6) Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
[15 paragraphs unchanged]
Unchanged: Expected output, Expected measurable benefits.
Objective for processing
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (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 NHS South, Central and West Commissioning Support Unit
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
- Population health management:
o Understanding the interdependency of care services
o Targeting care more effectively
o 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 South Central and West Commissioning Support Unit, Optum Health Solutions (UK) Ltd & NHS North and East London CSU.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The NHS Oxfordshire CCG involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
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 include high flyers.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
DARS-NIC-116582-F2F2J-v5.3 9 March 2020 to 8 March 2023
- Title
- DSfC - NHS Oxfordshire CCG; RS, 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
What changed from DARS-NIC-116582-F2F2J-v4.3
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
| Field | Was | Became |
|---|---|---|
| Start date | 2020-03-09 | |
| End date | 2023-03-08 |
Objective for processing
[4 paragraphs unchanged] Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit and Liaison Financial Services Ltd. Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost. [52 paragraphs unchanged]
Processing activities
[28 paragraphs unchanged]
• CCG of residence and/or registration.
• Patients who are resident and/or registered within the CCG region.
In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement.
A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting
Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation).
Microsoft UK supply IT infrastructure 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.
[12 paragraphs unchanged]
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.
[110 paragraphs unchanged]
Expected output
[7 paragraphs unchanged] 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 [62 paragraphs unchanged]
Expected measurable benefits
[11 paragraphs unchanged] 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 [42 paragraphs unchanged]
Objective for processing
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit and Liaison Financial Services Ltd.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (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 NHS South, Central and West Commissioning Support Unit
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
- Population health management:
o Understanding the interdependency of care services
o Targeting care more effectively
o 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 South Central and West Commissioning Support Unit & Optum Health Solutions (UK) Ltd
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The NHS Oxfordshire CCG involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
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 include high flyers.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
DARS-NIC-116582-F2F2J-v4.3 6 August 2019 to 5 August 2022
- Title
- DSfC - NHS Oxfordshire CCG; RS, 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
What changed from DARS-NIC-116582-F2F2J-v3.2
Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.
Objective for processing
[4 paragraphs unchanged]
Invoice Validation will be conducted by
South
NHS South,
Central and West Commissioning Support Unit
[2 paragraphs unchanged]
To conduct risk
stratification
stratification,
Secondary User Services (SUS+) data, identifiable at the level of NHS number
[54 words unchanged]
also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by
South
NHS South,
Central and West Commissioning Support Unit
[4 paragraphs unchanged]
-
Secondary Uses Service (SUS+)
[27 paragraphs unchanged]
-
Population health management:
•
o
Understanding the interdependency of care services
•
o
Targeting care more effectively
•
o
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
[15 words unchanged]
executed against linked de-identified data, and identification of future service delivery models
[2 paragraphs unchanged]
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The NHS Oxfordshire CCG involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Processing activities
[3 paragraphs unchanged]
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their
role.
role and the tasks that they are required to undertake.
[10 paragraphs unchanged]
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.
[17 paragraphs unchanged]
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the
South
NHS South,
Central and West Commissioning Support Unit.
[1 paragraph unchanged]
4.
South
NHS South,
Central and West Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes:
[5 paragraphs unchanged]
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between
South
NHS South,
Central and West Commissioning Support Unit CEfF team and the provider, meaning
[19 words unchanged]
management reporting detailing the total quantum of invoices received pending, processed etc.
[2 paragraphs unchanged]
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to
South
NHS South,
Central and West Commissioning Support Unit, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to
South
NHS South,
Central and West Commissioning Support Unit.
[2 paragraphs unchanged]
6. Once
South
NHS South,
Central and West Commissioning Support Unit has completed the processing, the CCG
[5 words unchanged]
via a secure connection to access the data pseudonymised at patient level
[30 paragraphs unchanged]
Data Processor 1 –
South
NHS South,
Central and West Commissioning Support Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS),
[41 words unchanged]
National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs) only is
securely transferred from
held within
the DSCRO
to South Central and West Commissioning Support Unit.
until the completion of points 2-8.
2.
South
NHS South,
Central and West Commissioning Support Unit
add derived fields, link data and provide analysis to:
receives GP Data as follows:
a. Identifiable GP data is submitted to NHS South, Central and West Commissioning Support Unit.
b. The identifiable data lands in a ring-fenced area for GP data only.
c. The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
d. There is a Data Processing Agreement in place between the GP and NHS South, Central and West Commissioning Support Unit. A specific named individual with NHS South, Central and West Commissioning Support Unit acts on behalf of the GP. This person has access to a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box. This software cannot be interrogated.
e. The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to that GP and to that specific date.
f. Identifiable data will only be processed by substantive employees of the data controller and processors. Before the CSU will receive the data from the ring fenced area, they require confirmation that the identifiable data has been deleted.
g. The CSU are then sent the pseudonymised GP data (into Database 2) with the pseudo algorithm specific to them.
h. Pseudonymised GP data is then linked to pseudonymised SUS data and an algorithm applied, also used for risk stratification. The outputs are then sent to Database 1.
3. NHS South, Central and West Commissioning Support Unit also receives a flow of social care data. Social Care data is received in one of the following 2 ways:
- Identifiable
a. Identifiable Social Care data is submitted to NHS South, Central and West Commissioning Support Unit.
b. The identifiable data lands in a ring-fenced area for Social Care data.
c. The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.
d. There is a Data Processing Agreement in place between the Local Authority and NHS South, Central and West Commissioning Support Unit. A specific named individual with NHS South, Central and West Commissioning Support Unit acts on behalf of the Local Authority. This person has access to a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box. This software cannot be interrogated.
e. The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to that Local Authority and to that specific date.
f. Identifiable data will only be processed by substantive employees of the data controller and processors. Before the CSU will receive the data from the ring fenced area, they require confirmation that the identifiable data has been deleted.
g. The CSU are then sent the pseudonymised social care data with the pseudo algorithm specific to them.
- Pseudonymised
a. The Social Care organisation is issued with their own black box solution.
b. The social care organisation requests a pseudonymisation key from the DSCRO. The key can only be used once is specific date to that date. The DSCRO is not involved in the processing of personal data for the purpose of pseudonymisation of social care data.
c. There is a Data Processing Agreement in place between the Provider and SCW CSU. A specific named individual with SCW CSU acts on behalf of the Provider.
d. The social care organisation submit the pseudonymised social care data to the CSU with the pseudo algorithm specific to them.
4. Once the pseudonymised GP data and social care data is received, the CSU make a request to the DSCRO.
5. The DSCRO checks the dates of the key generation (Point 2e and 3e/3b).
6. The DSCRO then sends a mapping table to the CSU.
7. The CSU then overwrite the organisation specific keys with the DSCRO key.
8. The mapping table is then deleted.
9. The pseudonymised data in point 1 is securely transferred from the DSCRO to NHS South, Central and West CSU.
10. Social care data and the outputs from Database 2 and GP data is then linked to the datasets listed within point 1.
11. NHS South, Central and West Commissioning Support Unit add derived fields, link data sets and provide analysis to.
[7 paragraphs unchanged]
3.
12.
Allowed linkage is between the data sets contained within point
1.
1, point 2 and point 3. No further linkage is permitted.
4. South
13. NHS South,
Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG.
5.
14.
Aggregation of required data for CCG management use will be completed by
South
NHS South,
Central and West Commissioning Support Unit or the CCG as instructed by the CCG.
6.
15.
Patient level data will not be shared outside of the CCG and
[34 words unchanged]
as set out within NHS Digital guidance applicable to each data set.
[13 paragraphs unchanged]
6) Patient level data will not be shared outside of the CCG
[22 words unchanged]
Sharing Agreement. External aggregated reports only with small number suppression can be
shared.
shared as set out within NHS Digital guidance applicable to each data set.
Data Processor 3 - Optum Health Solutions (UK) Ltd - for the NHS England Wave 2 PHM project
1) Pseudoymised SUS+, Mental Health Services Data Set (MHSDS), Community Services Data Set (CSDS), Local Provider data flows, GP Primary Care Data and Social Care Data is securely transferred from NHS Oxfordshire CCG to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national datasets and sent as individual data flows.
2) Optum Health Solutions (UK) Ltd provide analysis to:
o Whole population segmentation to assess population health needs
o Prospective risk scoring for individuals to indicate the likelihood of future adverse events
o Predictive modelling to determine individuals at risk and an understanding of the drivers of risk
o Longitudinal analysis of intersegmental drift - identifying individuals who move between complexity classifications and the drivers of these transitions
o The production of individual-level theographs to identify gaps in care
3) Allowed linkage is between the datasets contained with point (1) above. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and Local Provider Flows which contain only secondary care activity.
4) Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG.
5) Aggregation of required data for CCG management use will be completed by Optum health Solutions (UK) Ltd or the CCG as instructed by the CCG.
6) Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within the NHS Digital guidance applicable to each data set.
7) Optum Health Solutions (UK) Ltd will only be in receipt of data specified in Point 1 and only be permitted to act as Data Processors for the period specified in the NHS England contract with NHS Oxfordshire CCG.
8) The NHS England / Optum contractual period with NHS Oxfordshire CCG is anticipated to end in July/August 2020, at which point the data processor permissions for this project will be removed from this agreement by amendment.
Data held by Optum Health Solutions (UK) Ltd for the purpose of the NHS England Wave 2 PHM project will be destroyed within 6 months of the completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Expected output
[66 paragraphs unchanged] Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes. Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
Unchanged: Expected measurable benefits.
Objective for processing
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further.
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by NHS South, Central and West Commissioning Support Unit
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by NHS South, Central and West Commissioning Support Unit
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
- Population health management:
o Understanding the interdependency of care services
o Targeting care more effectively
o 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 South Central and West Commissioning Support Unit & Optum Health Solutions (UK) Ltd
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM project
NHS Oxfordshire CCG is working with NHS England as a Wave 2 Population Health Management CCG. NHS England has contracted Optum Health Solutions (UK) Ltd to work with selected CCGs to undertake population health and actuarial analysis to build up a methodology for dissemination across the NHS in England. The NHS Oxfordshire CCG involvement is for 20 weeks, anticipated to start in March 2020 for approximately 20 weeks. Data held by Optum Health Solutions (UK) Ltd for this project will be destroyed within 6 months of completion of the project and permissions as a data processor for this project will be removed from this agreement by amendment.
Expected output
Invoice Validation
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
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 include high flyers.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
Optum Health Solutions (UK) Ltd - NHS England Wave 2 PHM Project
The outputs, as part of the NHS England Wave 2 PHM national programme will identify patient cohorts and inequalities in outcome, spend and opportunity for further investigation, with a view to improving service delivery and patient health outcomes.
Wave 2 PHM will also begin to develop the CCG capability to undertake actuarial analysis of linked datasets from multiple care settings to develop further the understanding of the wider determinants of health across the population. All outputs will be delivered within the timescales of the contract between Optum Health Solutions (UK) Ltd and the CCG.
DARS-NIC-116582-F2F2J-v3.2 6 August 2019 to 5 August 2022
- Title
- DSfC - NHS Oxfordshire CCG; RS, 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 South Central and West Commissioning Support Unit
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) 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 South Central and West Commissioning Support Unit
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to highlight patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by South Central and West Commissioning Support Unit & Optum Health Solutions (UK) Ltd
Expected output
Invoice Validation
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.
Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
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 include high flyers.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patients are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
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. 7 versions: DARS-NIC-116582-F2F2J-v3.2, DARS-NIC-116582-F2F2J-v4.3, DARS-NIC-116582-F2F2J-v5.3, DARS-NIC-116582-F2F2J-v6.1, DARS-NIC-116582-F2F2J-v7.2, DARS-NIC-116582-F2F2J-v8.3, DARS-NIC-116582-F2F2J-v9.2
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October 2021
1 version added: DARS-NIC-116582-F2F2J-v10.3
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August 2022
1 version added: DARS-NIC-116582-F2F2J-v11.4
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October 2022
Succeeded Applicant organisation: NHS Oxfordshire CCG succeeded by NHS Buckinghamshire, Oxfordshire and Berkshire West ICB from 1 July 2022, according to NHS ODS. Not counted as a change.Succeeded Data controllers: NHS Oxfordshire CCG succeeded by NHS Buckinghamshire, Oxfordshire and Berkshire West 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-116582-F2F2J-v3.2, DARS-NIC-116582-F2F2J-v4.3, DARS-NIC-116582-F2F2J-v5.3, DARS-NIC-116582-F2F2J-v6.1, DARS-NIC-116582-F2F2J-v7.2 — 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-116582-F2F2J, “DSfC - NHS Oxfordshire CCG and Oxfordshire County Council; Comm.”. Read via NHS Data Access Explorer (unofficial), https://healthdatauses.uk/agreements/dars-nic-116582-f2f2j/ (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-116582-F2F2J to see the original rows.