NHS Digital Data Release Register - reformatted
NHS Bedfordshire, Luton And Milton Keynes CCG projects
- GDPPR COVID-19 CCG - Pseudo
- DSfC NHS Bedfordshire, Luton and Milton Keynes CCG
- DSfC - NHS Luton CCG IV, Comm
- DSfC - NHS Bedfordshire CCG - IV & Comm
- DSfC - NHS Milton Keynes CCG - IV, Comm.
- DSfC - NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG - Comm
- DSfC - NHS Milton Keynes CCG - RS
- DSfC - NHS Bedfordshire CCG - RS
- GDPPR COVID-19 CCG - Pseudo
- GDPPR COVID-19 CCG - Pseudo
- GDPPR COVID-19 CCG - Pseudo
- DSfC - NHS Milton Keynes CCG - Comm
231 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
🚩 NHS Bedfordshire, Luton And Milton Keynes CCG was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Bedfordshire, Luton And Milton Keynes CCG may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.
GDPPR COVID-19 CCG - Pseudo — DARS-NIC-433166-T6N9F
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent)
Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2021-04-01 — 2021-09-30 2021.03 — 2021.05.
Access method: One-Off, Frequent Adhoc Flow
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- GPES Data for Pandemic Planning and Research (COVID-19)
- COVID-19 Ethnic Category Data Set
- COVID-19 Vaccination Status
- COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
Objectives:
NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals.
GPES data for pandemic planning and research (GDPPR COVID 19)
To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the COVID-19 Directions.
The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patient’s GP record, such as details of:
• diagnoses and findings
• medications and other prescribed items
• investigations, tests and results
• treatments and outcomes
• vaccinations and immunisations
Details of any sensitive SNOMED codes included in the GDPPR data set can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data.
There are no free text record entries in the data.
The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes.
Such uses of the data include but are not limited to:
• Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact and to estimate when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions.
• Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified.
• Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions:
The data may only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data.
The linked data may only be used for purposes stipulated within this agreement and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. Reidentification of individuals is not permitted under this DSA.
LEGAL BASIS FOR PROCESSING DATA:
Legal Basis for NHS Digital to Disseminate the Data:
NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice).
The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI.
Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes.
Legal Basis for Processing:
The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2).
The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information:
Health organisations
“Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area
The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include:
• persons employed or engaged for the purposes of the health service
Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population.
Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures.
Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.
Expected Benefits:
• Manage demand and capacity
• Reallocation of resources
• Bring in additional workforce support
• Assists commissioners to make better decisions to support patients
• Identifying COVID-19 trends and risks to public health
• Enables CCGs to provide guidance and develop policies to respond to the outbreak
• Controlling and helping to prevent the spread of the virus
Outputs:
• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients due to the impact of COVID-19
• Analysis of resource allocation
• Investigating and monitoring the effects of COVID-19
• Patient Stratification in relation to COVID-19, such as:
o Patients at highest risk of admission
o Frail and elderly
o Patients that are currently in hospital
o Patients with prescriptions related to COVID-19
o Patients recently Discharged from hospital
For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.
Processing:
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
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.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).
The Recipients will take all required security measures to protect the disseminated data and they will not generate copies of their cuts of the disseminated data unless this is strictly necessary. Where this is necessary, the Recipients will keep a log of all copies of the disseminated data and who is controlling them and ensure these are updated and destroyed securely.
Onward sharing of patient level data is not permitted under this agreement. Only aggregated reports with small number suppression can be shared externally.
The data disseminated will only be used for COVID-19 GDPPR purposes as described in this DSA, any other purpose is excluded.
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.
AUDIT
All access to data is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms.
Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI.
DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below:
• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner area).
and/or
• Patients treated by a provider where the CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the CCG.
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
- GDPPR COVID 19 Data
Pseudonymisation is completed within the DSCRO and is then disseminated as follows:
1. Pseudonymised GDPPR COVID 19 data is securely transferred from the DSCRO to the Data Controller / Processor
2. Aggregation of required data will be completed by the Controller (or the Processor as instructed by the Controller).
3. Patient level data may not be shared by the Controller (or any of its processors).
DSfC NHS Bedfordshire, Luton and Milton Keynes CCG — DARS-NIC-422183-C3K9L
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld, Anonymised - ICO Code Compliant, Identifiable (Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))
Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information', National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2021-04-01 — 2024-03-31 2021.03 — 2021.05.
Access method: One-Off, Frequent Adhoc Flow
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No, Yes
Datasets:
- Acute-Local Provider Flows
- Ambulance-Local Provider Flows
- Children and Young People Health
- Civil Registration - Births
- Civil Registration - Deaths
- Community Services Data Set
- Community-Local Provider Flows
- Demand for Service-Local Provider Flows
- Diagnostic Imaging Dataset
- Diagnostic Services-Local Provider Flows
- Emergency Care-Local Provider Flows
- e-Referral Service for Commissioning
- Experience, Quality and Outcomes-Local Provider Flows
- Improving Access to Psychological Therapies Data Set
- Maternity Services Data Set
- Medicines dispensed in Primary Care (NHSBSA data)
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- Mental Health-Local Provider Flows
- National Cancer Waiting Times Monitoring DataSet (CWT)
- National Diabetes Audit
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Patient Reported Outcome Measures
- 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
- SUS for Commissioners
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Adult Social Care
- Improving Access to Psychological Therapies Data Set_v1.5
- Civil Registrations of Death
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DID)
- Improving Access to Psychological Therapies (IAPT) v1.5
- Mental Health and Learning Disabilities Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Services Data Set (MHSDS)
- Patient Reported Outcome Measures (PROMs)
- Summary Hospital-level Mortality Indicator (SHMI)
Objectives:
INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so the CCG is able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) 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
The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.
Invoice Validation will be conducted by Liaison Financial Services Ltd, NHS Arden and GEM CSU and NHS Bedfordshire, Luton and Milton Keynes CCG.
Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.
RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification, Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for both individual and groups of vulnerable patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Ltd
COMMISSIONING
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)
- e-Referral Service (eRS)
- Personal Demographics Service (PDS)
- Summary Hospital-level Mortality Indicator (SHMI)
- Medicines Dispensed in Primary Care (NHSBSA Data)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to highlight cohorts of patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.
Support measuring the health, mortality or care needs of the total local population.
Provide intelligence about the safety and effectiveness of medicines.
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. The added GP linkage will enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.
Processing for commissioning will be conducted by NHS Arden and GEM Commissioning Support Unit, NHS North and East London Commissioning Support Unit, NHS South, Central and West Commissioning Support Unit, RSR Consultants Ltd, AH Analysis, Optum Health Solutions (UK) Ltd and Circle Health.
Circle Health - this processing allows for the correct charging mechanisms to be applied across the local healthcare system thereby facilitating efficient use of public monies which can support the delivery of frontline healthcare in the local area.
RSR Consultants Ltd - processes the data to help to identify changes that are most likely changes in how activity is coded and counted rather than changes in patient care as well as help understand the likely financial impact. They also provide additional capacity for general commissioning reporting
AH Analysis Ltd currently analyses local data flows including Service Level Agreement Manager data within NHS Bedfordshire, Luton and Milton Keynes CCG and are therefore listed as a data processor. They supply support to the system, and will need to be a data processor going forward with access to SUS data flows. This will ensure they can support the development of Population Health analytics.
Expected Benefits:
INVOICE VALIDATION
The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by:
1. Ensuring that activity is fully financially validated.
2. Ensuring that service providers are accurately paid for the patients treatment.
3. Enabling services to be planned, commissioned, managed, and subjected to financial control.
4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they are responsible.
5. Fulfilling commissioners duties to fiscal probity and scrutiny.
6. Ensuring full financial accountability for relevant organisations.
7. Ensuring robust commissioning and performance management.
8. Ensuring commissioning objectives do not compromise patient confidentiality.
9. Ensuring the avoidance of misappropriation of public funds.
RISK STRATIFICATION
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early intervention.
3. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care.
5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes
All of the above lead to improved patient experience and health outcomes through more effective commissioning of services.
COMMISSIONING
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
19. Assists commissioners to make better decisions to support patients and drive changes in health care
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
23. Monitoring of entire population, as a pose to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
27. Understand admissions linked to overprescribing.
28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
Circle Health
1. Allows correct charging mechanisms to be applied across the local healthcare system
RSR Consultants Ltd
1. Identify changes that are most likely changes in how activity is coded and counted rather than changes in patient care
2. help understand the likely financial impact in coding changes
AH Analysis Ltd
1. Deliver reporting for all aspects of patient level care mainly delivered by large NHS providers (but not limited to) for example urgent care, by tracking the full pathway of services/charge points
2. Moving forward they will track Quality, Innovation, Productivity and Prevention (QIPP) schemes at code level (OPCS or ICD10 depending on scheme) as SLAM aggregated billing if often too summarised for the schemes. SLAM provides the insight to price, monitor and manage activities and costs in line with contract requirements. It unifies activity and price data sets across health settings to deliver efficient, transparent and consistent expenditure control
This supports commissioning transformation programmes, including Heat Interface Unit respiratory reporting on patient volumes and complexity, all reported at aggregated level.
3. They will also use The Secondary Uses Service (SUS) and SLAM to create Population Health reporting to facilitate Primary Care Networks (PCN) development workstreams and support system management with advanced analytics capability.
Outputs:
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.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts.
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)
RSR Consultants Ltd
It is important that the limited resources available to the NHS are utilised in the best way possible for patient care. NHS England have set out, via the NHS Standard Contract, that changes in coding and counting are locally notified so that changes in how patient care are reported are:
1. identified as changes in coding and counting rather than changes in actual care
2. locally discussed to ensure they are valid changes and
3. any financial impact from the change is neutralised for the required amount of time so that the financial impact can be properly planned for.
Circle Health -
Line level data is converted into pivot table which summarises commissioned activity by speciality, HRG subchapter and activity type (outpatient/inpatient).
AH Analysis Ltd
1. Provides the monthly challenge process - running Structured Query Language (SQL) on SUS data to establish counting and coding queries. This ensures the CCG can query the level of detail it wishes to check as opposed to generic CSU packages.
2. Run the analytics for the CCG including Deep Dives for acute activity trends year on year actuals whereby using SUS to append age analysis, outcomes and Length Of Stay (LOS) to the SLAM billing data all of which is at an aggregated level to explain the story and why finances maybe affected adversely. The LOS is a length of stay which we can only usually obtain in SUS as local flows have started to exclude this due to the file sizes In addition LOS helps the CCG to look at for example patients admitted from Accident & Emergency with short LOS, this may be down to hospital flows and meeting their constitutional targets 4 hour wait
3. Provide full Primary Care Network (PCN) GP reporting to look at A&E slot attendance use by practice/locality, planned care volumes over time etc to support system management.
4. Also reconcile SUS to SLAM for assurance purposes which is standard reconciliation practice on acute contracts.
Ultimately the CCGs patients will benefit from improved pathways and service integration further to better decision making as a result of the provision of enhanced analytics. AH Analysis Ltd will require access all the data for the CCG where it can develop population health management analytics. This will support the CCG’s preventative care programme across primary care and the CCG's population health management initiatives. The CCG anticipate the need to use data at its lowest level to facilitate this agenda and for AH Analysis Ltd to actively support key workstreams owing to their expertise. This will support the development of the Integrated Care System (ICS) and enable decision makers to determine the best use of resource for their patient population, make best use of resources and reshape the way contracts are designed. AH Analysis Ltd will act as an enabler to provide the detailed analytics which enable the CCG to improve patient care and outcomes through the analysis and aggregation of such data.
Processing:
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.
Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
The identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.
ONWARD SHARING:
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.
Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.
SEGREGATION:
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.
Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.
All access to data is auditable by NHS Digital.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.
DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below. This also includes the purpose on which they would be applied -
For the purpose of Commissioning:
• Patients who are normally registered and/or resident within the NHS Bedfordshire, Luton and Milton Keynes CCG region (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where NHS Bedfordshire, Luton and Milton Keynes 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 Bedfordshire, Luton and Milton Keynes CCG - this is only for commissioning and relates to both national and local flows.
For the purpose of Risk Stratification:
• Patients who are normally registered and/or resident within the NHS Bedfordshire, Luton and Milton Keynes CCG region (including historical activity where the patient was previously registered or resident in another commissioner
For the purpose of Invoice Validation:
• Patients who are resident and/or registered within the CCG region.
This includes data that was previously under a different organisation name but has now merged into this CCG
In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement.
A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting
Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation).
Microsoft Limited provide cloud services for NHS North East London Commissioning Support Unit, NHS Arden and Greater Eastern Midlands Commissioning Support Unit, Liaison Financial Services Ltd, Optum Health Solutions UK Ltd and NHS 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 databases containing the data.
Amazon Web Services provide cloud services for Optum Health Solutions UK Ltd 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 databases containing the data.
NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by Salford Royal NHS Foundation Trust ) supply IT infrastructure for Arden and GEM Commissioning Support Unit and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
University Hospitals Bristol NHS Foundation Trust, Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust, Interxion and The Bunker 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.
INVOICE VALIDATION
CCG- NHS Arden and GEM CSU and NHS Bedfordshire, Luton and Milton Keynes CCG
1. Identifiable SUS+ Data is obtained by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) located in the CCG.
3. The CEfF also receive backing data from the provider.
4. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.
b. Once the provider backing information is received, it will be checked against national NHS and local commissioning policies, as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. In relation to a patient registered with the CCG, GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved.
Liaison Financial Services Ltd
1. Identifiable SUS+ Data is obtained by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) 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 Service 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
NHS Arden and Gem CSU
1. Identifiable SUS+ Data is obtained by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the NHS Arden and Gem CSU.
3. The CEfF also receive backing data from the provider.
4. NHS Arden and Gem CSU 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 Arden and Gem CSU CEfF team and the provider, meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.
RISK STRATIFICATION
Prescribing Services Ltd
1. Identifiable SUS+ data is transferred to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to Prescribing Services Ltd, who securely hold the SUS+ data.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level
COMMISSIONING
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
12. Civil Registries Data (CRD) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
DATA PROCESSOR 1,2 and 3- South Central & West Commissioning Support Unit (SCW CSU), North and East London Commissioning Support Unit (NEL CSU) and NHS Arden and Greater East Midlands Commissioning Support Unit (Arden and GEM CSU)
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI) and Medicines Dispensed in Primary Care (NHSBSA Data) data only is securely transferred from the DSCRO to SCW CSU, NEL CSU and Arden and GEM CSU
2. SCW CSU, NEL CSU and Arden and GEM CSU add derived fields by using existing data, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. SCW CSU, NEL CSU and Arden and GEM CSU then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregation of required data for CCG management use will be completed by SCW CSU, NEL CSU and Arden and GEM CSU or the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
North East London Commissioning Support Unit also receive identifiable GP data for a GP Practices within the CCGs area. The GP data is received and process as per points i-iv below.
i. Identifiable GP data is extracted from consented GP practices Principal Clinical System via NEL-hosted IM1 GP Extraction service.
ii. Extracted data lands on secure North and East London Commissioning Support Unit GP Environment where strict access is limited to individuals who have been authorised by North and East London DSCRO Business Lead or Senior Information Risk Owner and act on behalf of the Data Controller (GP Practice).
iii. The North and East London Commissioning Support Unit Pseudonym is then applied to GP data within Secure GP Data Environment via a Black Box function. The pseudonymisation enables the linkage with other data sets specified in this DSA.
iv. The agreed specification of Pseudonymised GP data is then made available to CCGs via a secure means of transfer from the secure North and East London Commissioning Support Unit GP environment to the destination CCG or Commissioning Support Unit environment where only pseudonymised data resides.
Data Processor 4-RSR Consultants Limited
1. Pseudonymised SUS+ only is securely transferred from the DSCRO to NHS Bedfordshire, Luton and Milton Keynes CCG.
2. NHS Bedfordshire, Luton and Milton Keynes CCG conduct calculations and provide a subset of pseudonymised SUS to RSR Consultants Limited. (A subset of pseudo SUS data is passed to RSR Consultants Limited without any calculations)
3. RSR Consultants Limited provide analysis.
4. RSR Consultants Limited then pass the processed, pseudonymised data to the CCG.
5. Aggregation of required data for CCG management use will be completed by RSR Consultants Limited or the CCG as instructed by the CCG. (Aggregation is provided by RSR)
6. 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 5-Circle Health Limited
1. Pseudonymised SUS+ only is securely transferred from the DSCRO to NHS Bedfordshire, Luton and Milton Keynes CCG .
2. Once the pseudonymised data is available to the CCG, data from the assigned database and extract detail relating to Musculoskeletal (MSK) activities will then be shared with Circle Health by sending an excel version of the data through NHS.net along with a calculation of the proposed recharge to Database be invoiced
3. Circle Health then validate the calculation of the recharge and on agreement with the CCG, an appropriate invoice can be raised
4. Aggregation of required data for CCG management use will be completed by Circle Health or the CCG as instructed by the CCG. (Aggregate data is provided by CCG in this case)
5. 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 6 -AH Analysis Ltd - Routine/standard SUS queries using Service Level Agreement Manager (SLAM) and SUS data.
1. Pseudonymised SUS+ only is securely transferred from the DSCRO to NHS Bedfordshire, Luton and Milton Keynes CCG .
2. AH Analysis Ltd use data from the CCG data warehouse which has been supplied by DSCRO (CSU) and only aggregated non PID (personal identifiable data) into CIVICA to perform multiple analytics to explain the position and issues to contracts, finance and commissioners across the CCG. (AH Analysis Ltd processes non-PID Patient Level Data SLAM data in CIVICA to produce required reports)
3. Results of the processing are then made available to the CCG
4. AH Analysis Ltd will use Pseudonymised Patient Level Data SUS data from NHS Bedfordshire, Luton and Milton Keynes CCG Data Warehouse to produce regular SUS reporting for different teams in CCG which will support the Integrated Care System workstreams and wider Population Health reporting and analytics requirements
5. 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 7 Optum Health Solutions (UK) Limited
1. NHS Bedfordshire, Luton and Milton Keynes CCG securely pass pseudonymised SUS, Community Services Data Set (CSDS), Mental Health Services Data Set, Local Provider data and GP Primary Care data only to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national data sets and sent as individual data flows
2. Optum Health Solutions (UK) Ltd provide analysis to:
a. Whole population segmentation to assess population health needs
b. Prospective risk scoring for individuals at risk and an understanding of the drivers of the risk
c. Predictive modelling to determine individuals at risk and an understanding of the drivers of the risk
d. Longitudinal analysis of intersegmental drift - identifying individuals who move between complexity classifications and the drivers of these transitions
e. The production of individual level theographs to identify gaps in care.
3. Allowed linkage is between the datasets contained within point (1) above. GP data, CSDS and Mental Health Services datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.
4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregated required data for CCG Management use will be completed by Optum Health Solutions (UK) Ltd or to the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis as per the purposes stipulated with the data sharing agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each dataset.
7. Optum Health Solutions (UK) Ltd will only be in receipt of data and only be permitted to act as Data Processors for the period specified in the contract with the CCG.
DSfC - NHS Luton CCG IV, Comm — DARS-NIC-55670-P9Z0Z
Type of data: information not disclosed for TRE projects
Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld, Anonymised - ICO Code Compliant, Identifiable (Section 251, Section 251 NHS Act 2006, Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))
Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2019-08-23 — 2022-08-22 2018.06 — 2021.03.
Access method: Frequent adhoc flow, Frequent Adhoc Flow, One-Off
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- Acute-Local Provider Flows
- Ambulance-Local Provider Flows
- Community Services Data Set
- Community-Local Provider Flows
- Demand for Service-Local Provider Flows
- Diagnostic Imaging Dataset
- Diagnostic Services-Local Provider Flows
- Emergency Care-Local Provider Flows
- Experience, Quality and Outcomes-Local Provider Flows
- Improving Access to Psychological Therapies Data Set
- Maternity Services Data Set
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- Mental Health-Local Provider Flows
- National Cancer Waiting Times Monitoring DataSet (CWT)
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Population Data-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Public Health and Screening Services-Local Provider Flows
- SUS for Commissioners
- Children and Young People Health
- Civil Registration - Births
- Civil Registration - Deaths
- National Diabetes Audit
- Patient Reported Outcome Measures
- e-Referral Service for Commissioning
- Personal Demographic Service
- Summary Hospital-level Mortality Indicator
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Improving Access to Psychological Therapies Data Set_v1.5
- Civil Registrations of Death
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DID)
- Improving Access to Psychological Therapies (IAPT) v1.5
- Mental Health and Learning Disabilities Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Services Data Set (MHSDS)
- Patient Reported Outcome Measures (PROMs)
- Summary Hospital-level Mortality Indicator (SHMI)
Objectives:
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 they 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 and will not be used further.
Invoice Validation with be conducted by NHS Luton CCG
The CCG are advised by the CEfF team whether payment for invoices can be made or not.
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)
The pseudonymised data is required to for the following purposes:
§ Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
§ Data Quality and Validation – allowing data quality checks on the submitted data
§ Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§ Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§ Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North and East London CSU.
Yielded Benefits:
Expected Benefits:
Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
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 re admissions, 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.
Outputs:
Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events
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
Processing:
Data must only be used as stipulated within this Data Sharing Agreement.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
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.
All access to data is managed under Roles-Based Access Controls
No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality and that data required by the applicant.
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)
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.
All access to data is auditable by NHS Digital.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.
Invoice Validation
1. Identifiable SUS+ Data is obtained from the SUS+ Repository by the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) located in the CCG.
3. The CEfF conduct the following processing activities for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the 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. In relation to a patient registered with the CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
4. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved
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)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – North and East London CSU
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) and National Cancer Waiting Times Monitoring Data Set (CWT) only is securely transferred from the DSCRO to North and East London CSU.
2. North and East London CSU add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. North and East London CSU then pass the processed, pseudonymised and linked data to the CCG.
5. Aggregation of required data for CCG management use will be completed by North and East London CSU or the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.
DSfC - NHS Bedfordshire CCG - IV & Comm — DARS-NIC-49738-Q2B0D
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld, No - DSfC for Invoice Validation Purposes, Anonymised - ICO Code Compliant, Identifiable (Section 251, Section 251 NHS Act 2006, Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))
Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(7), Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive
When:DSA runs 2018-12-01 — 2021-11-30 2018.06 — 2021.03.
Access method: Frequent adhoc flow, Frequent Adhoc Flow, One-Off
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- Acute-Local Provider Flows
- Children and Young People Health
- Community Services Data Set
- Community-Local Provider Flows
- Demand for Service-Local Provider Flows
- Diagnostic Imaging Dataset
- Diagnostic Services-Local Provider Flows
- Emergency Care-Local Provider Flows
- Experience, Quality and Outcomes-Local Provider Flows
- Improving Access to Psychological Therapies Data Set
- Maternity Services Data Set
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- Mental Health-Local Provider Flows
- National Cancer Waiting Times Monitoring DataSet (CWT)
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Population Data-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Public Health and Screening Services-Local Provider Flows
- Ambulance-Local Provider Flows
- SUS for Commissioners
- Civil Registration - Births
- Civil Registration - Deaths
- e-Referral Service for Commissioning
- National Diabetes Audit
- Patient Reported Outcome Measures
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Improving Access to Psychological Therapies Data Set_v1.5
- Civil Registrations of Death
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DID)
- Improving Access to Psychological Therapies (IAPT) v1.5
- Mental Health and Learning Disabilities Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Services Data Set (MHSDS)
- Patient Reported Outcome Measures (PROMs)
Objectives:
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 they 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 and will not be used further.
Invoice Validation with be conducted by South Central & West Commissioning Support Unit
The CCG are advised by South Central & West Commissioning Support Unit whether payment for invoices can be made or not.
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)
The pseudonymised data is required to for the following purposes:
§ Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
§ Data Quality and Validation – allowing data quality checks on the submitted data
§ Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§ Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§ Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North East London Commissioning Support Unit, Mede Analytics and South Central & West Commissioning Support Unit
National identifiers will be removed by NHS Digital (DSCRO) using MedeAnalytics’ Pseudonymisation at Source process, prior to data leaving NHS Digital. By using the MedeAnalytics process, the resulting de-identified data can be linked within the MedeAnalytics system with data from other providers (as specified in this application) using the same process, without the need for identifiable data to flow to MedeAnalytics .
Further, as national identifiers are removed by NHS Digital before transmission, thus together with other approaches rendering the data Anonymous in line with the ICO’s anonymisation code of practice, the resulting, non-identifiable data representing 100% of the commissioner’s records is suitable for General Commissioning and Contract Validation purposes, both of which have been previously approved. As data Is anonymous in context, there is no need to remove records for type 2 objectors, as the records are no longer identifiable when they leave the protected NHS Digital environment.
Where analysis of pseudonymised patient records show that the associated patients could benefit from clinical interventions, GP Practice users who have legitimate relationships with the patients will be able to re-identify the patient records so that they can provide the interventions (direct care).
Yielded Benefits:
The CCG has realised the measurable benefits for the data collection and the viable evaluation data has enabled services to be delivered to match the population requirements whilst planning for future needs. This work will continue year on year to match the delivery/funding of targets services for the population. The QIPP Project Management Office (PMO) is where we used the process to identify the activity within contracts at a detailed level and set phased plans to then monitor against in year. This saved the PMO team the labour resource of aggregating many reports as all QIPPs relating to acute contracts were within the one output from our process. This assisted the CCG to set, monitor and track progress of schemes in a timely way each month to assure itself that it could meet its transformation requirements and change the ways in which care was being delivered. In addition, this monitoring helps identify new areas of QIPP that can be targeted moving forward, thus quickly identifying areas of concern.
Expected Benefits:
Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
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.
Outputs:
Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events
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
Processing:
Processing activities:
Data must only be used as stipulated within this Data Sharing Agreement.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
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.
All access to data is managed under Roles-Based Access Controls
No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality and that data required by the applicant.
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)
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.
All access to data is auditable by NHS Digital.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.
Data Minimisation
Data Minimisation in relation to the data sets listed within section 3 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 commissioner (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where the commissioner 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 the commissioner - this is only for commissioning and relates to both national and local flows.
For the purpose of Invoice Validation:
• CCG of residence and/or registration.
The above relates to data requested only (Table 3B). Data currently held (Table 3A) will have the following Data Minimisation:
• CCG of residence and/or registration.
For clarity, any access by Interxion to data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Invoice Validation
1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the South Central & West Commissioning Support Unit.
3. South Central & West Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the 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.
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between South Central & West Commissioning Support UnitCEfF 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.
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)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Commissioning
The North East London Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1) SUS
2) Local Provider Flows (received directly from providers)
a. Ambulance
b. Demand for Service
c. Diagnostic Service
d. Emergency Care
e. Experience, Quality and Outcomes
f. Mental Health
g. Other Not Elsewhere Classified
h. Population Data
i. 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) Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO using the Medeanalytics pseudonymisation tool and is then disseminated as follows:
1) Pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North East London Commissioning Support Unit for landing only.
2) North East London Commissioning Support Unit then pass the processed, Pseudonymised data provided under DSCRO contracts to the CCGs data processor, Medeanalytics International Limited where it is received, stored and processed
3) Records contain no national identifiers, but do contain the following local identifiers: [Local Patient Identifier], [Hospital Provider Spell No], [Unique CDS Identifier], [Attendance Identifier], and [A&E Attendance Number]
4) On arrival at Medeanalytics International Limited, one of the Medeanalytics International Limited operational staff then transfers the data from the secure landing zone to the ETL process. The Extract Transform Load (ETL) process then loads the data into the Medeanalytics International Limited system, where it is linked.
5) Allowed linkage is between the data sets contained within point 1 and the following data that is pseudonymised at source using the Medeanalytics pseudonymisation tool:
o Social Care data
o GP Practice data
o Community data
o Mental Health data
6) Access is fully controlled by Role Based Access Control (RBAC),, signed off by Caldicott Guardians/SIROs.
7) CCGs use the workflow features provided by the Medeanalytics International Limited Contract Validation Module to check recorded activity against contracts, and facilitate contract discussions with providers
8) CCG users use online features of the Medeanalytics International Limited system to produce reports, charts and dashboards to analyse the data for the purposes listed.
9) Pseudonymised 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 with access fully controlled by RBAC, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared.
Segregation
Data is held within the MedeAnalytics system, and is segregated according to contract.
Only MedeAnalytics operational staff (currently 4 individuals operating under full time MedeAnalytics employment contracts) have access to data prior to loading into the main system.
All staff at MedeAnalytics undertake compulsory IG Toolkit training every year.
All MedeAnalytics staff understand their responsibilities with regard to receiving, storage, processing and handling of data, and contractual sanctions that can result in disciplinary actions including dismissal for contraventions are included in employee contracts.
Specific processes are in place to setup new system users, all of which require Caldicott Guardian or SIRO sign-off in order to obtain user identities and passwords. Identities and passwords are restricted to specific subsets of data according to their Roles, so that a CCG user can only see data for their own CCG, and a GP user can only see data for their own GP Practice.
All access to data is managed under Roles-Based Access Controls
Access to data is provided through the MedeAnalytics front end interfaces, for on-line access; while it is reasonable and allowable for users to export the results displayed in reports, charts and dashboards, so that the results can be used in board presentations, reports and other management documents, bulk export of underlying linked data sets is not possible.
All accesses are audited
CCG staff are only able to access data pertinent to their own CCG
GP Practice staff are only able to access data for patients registered to their own practice
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management service (operated by BMS) that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
Only GP Practice users are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify have access to encrypted data, and can only access data to which they have rights under RBAC (which is CG/SIRO approved– within the CCG)
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.
Commissioning – Pseudonymised – Local Flows
Management of services for non-contracted activities
The South Central and West Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1) Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Diagnostic Service
e. Primary Care Services
f. 3rd Party commissioning
Data quality management and pseudonymisation is completed within the DSCRO is then disseminated as follows:
1) Pseudonymised Local Provider data only is securely transferred from the DSCRO to South Central and West Commissioning Support Unit.
2) CCG staff then download the processed, Pseudonymised data from the South Central and West Commissioning Support Unit transfer service, and will then delete the data from the transfer service. The CCG analyse the data to see patient journeys for pathways or service design, re-design and commissioning.
3. Aggregation of required data for CCG management use will be completed by the CCG.
4. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreements
5. CCG staff then log in to the South Central and West Commissioning Support Unit transfer service and download the data to the CCG’s systems. South Central and West Commissioning Support Unit staff then delete the data from the transfer service.
DSfC - NHS Milton Keynes CCG - IV, Comm. — DARS-NIC-47118-L9M1G
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld, No - DSfC for Invoice Validation Purposes, Anonymised - ICO Code Compliant, Identifiable (Section 251, Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(7), Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2019-07-28 — 2022-07-27 2018.10 — 2021.03.
Access method: Frequent Adhoc Flow, One-Off
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- Acute-Local Provider Flows
- Ambulance-Local Provider Flows
- Children and Young People Health
- Community Services Data Set
- Community-Local Provider Flows
- Demand for Service-Local Provider Flows
- Diagnostic Imaging Dataset
- Diagnostic Services-Local Provider Flows
- Emergency Care-Local Provider Flows
- Experience, Quality and Outcomes-Local Provider Flows
- Improving Access to Psychological Therapies Data Set
- Maternity Services Data Set
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- Mental Health-Local Provider Flows
- National Cancer Waiting Times Monitoring DataSet (CWT)
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Population Data-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Public Health and Screening Services-Local Provider Flows
- SUS for Commissioners
- Civil Registration - Births
- Civil Registration - Deaths
- National Diabetes Audit
- Patient Reported Outcome Measures
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Improving Access to Psychological Therapies Data Set_v1.5
- Civil Registrations of Death
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DID)
- Improving Access to Psychological Therapies (IAPT) v1.5
- Mental Health and Learning Disabilities Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Services Data Set (MHSDS)
- Patient Reported Outcome Measures (PROMs)
Objectives:
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 they 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 and will not be used further.
The legal basis for this to occur is under Section 251 of NHS Act 2006.
Invoice Validation with be conducted by:
NHS Arden & Greater East Midlands Commissioning Support Unit.
The CCG are advised by the CSU whether payment for invoices can be made or not.
Commissioning
To use pseudonymised data to provide intelligence to support commissioning of health services. 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.
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)
- Diagnostic Imaging Data Set (DIDS)
- Community Services Data Set (CSDS)
- National Cancer Waiting Times Data Set (NCWT)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The 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:
- Arden and Greater East Midlands Commissioning Support Unit
- Optum Health Solutions Limited.
Yielded Benefits:
N/A
Expected Benefits:
Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
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. 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.
Outputs:
Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events
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.
Processing:
Data must only be used as stipulated within this Data Sharing Agreement.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
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.
All access to data is managed under Roles-Based Access Controls
No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality and that data required by the applicant.
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)
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.
All access to data is auditable by NHS Digital.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.
Invoice Validation
1. Identifiable SUS Data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
- The DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the Arden and Greater East Midlands Commissioning Support Unit .
2. The CSU carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the SUS data flow to validate the corresponding record in the backing data flow
b. Once the 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.
3. 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 Arden and Greater East Midlands 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.
Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS
2. Local Provider Flows (received directly from providers)
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
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. Diagnostic Imaging Data Set (DIDS)
10. Community Services Data Set (CSDS)
11. National Cancer Waiting Times Data Set (NCWT)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor – Arden and Greater East Midlands 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) Diagnostic Imaging data (DIDS)Community Services Data Set (CSDS) and National Cancer Waiting Times Data Set (NCWT) only is securely transferred from the DSCRO to Arden and Greater East Midlands Commissioning Support Unit.
2) Arden and Greater East Midlands Commissioning Support Unit add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3) Allowed linkage is between the data sets contained within point 1.
4) Arden and Greater East Midlands Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
5) Aggregation of required data for CCG management use will be completed by Arden and Greater East Midlands Commissioning Support Unit or the CCG as instructed by the CCG.
6) Patient level data will not be shared outside of the 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.
Data Processor 2 – Arden and Greater East Midlands Commissioning Support Unit
1) Pseudonymised SUS and Local Provider data only is securely transferred from the DSCRO to Optum Health Solutions Limited.
2) Optum Health Solutions Limited add derived fields, link data and provide analysis.
3) Allowed linkage is between the data sets contained within point 1.
4) Optum Health Solutions Limited then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
5) Aggregation of required data for CCG management use will be completed by Optum Health Solutions Limited 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
DSfC - NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG - Comm — DARS-NIC-338789-M0T3Q
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data)
Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2019-11-15 — 2022-11-14 2019.12 — 2021.03.
Access method: Frequent Adhoc Flow, One-Off
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- Acute-Local Provider Flows
- Ambulance-Local Provider Flows
- Children and Young People Health
- Civil Registration - Births
- Civil Registration - Deaths
- Community Services Data Set
- Community-Local Provider Flows
- Demand for Service-Local Provider Flows
- Diagnostic Imaging Dataset
- Diagnostic Services-Local Provider Flows
- Emergency Care-Local Provider Flows
- Experience, Quality and Outcomes-Local Provider Flows
- Improving Access to Psychological Therapies Data Set
- Maternity Services Data Set
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- Mental Health-Local Provider Flows
- National Cancer Waiting Times Monitoring DataSet (CWT)
- National Diabetes Audit
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Patient Reported Outcome Measures
- Population Data-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Public Health and Screening Services-Local Provider Flows
- SUS for Commissioners
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Improving Access to Psychological Therapies Data Set_v1.5
- Civil Registrations of Death
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DID)
- Improving Access to Psychological Therapies (IAPT) v1.5
- Mental Health and Learning Disabilities Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Services Data Set (MHSDS)
- Patient Reported Outcome Measures (PROMs)
Objectives:
NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG work jointly across the region to fulfil their commissioning functions. The CCGs will work proactively and collaboratively with each other to redesign services across boundaries to integrate services.
The CCGs will 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 geographical region.
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 pseudonymised data is required 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 CCGs area based on the full analysis of multiple pseudonymised datasets.
Data will be shared between the three joint data controllers. Rather than sharing full datasets, most of the time, it may be selected reports that will be shared. These reports will be at record level rather than aggregated with small number suppression. On occasions, the reports may include the data that sits behind the reports.
Working collaboratively, there may be occasions where one CCG takes the lead on specific region wide analysis, providing outcomes to the other two. The CCGs are able to conduct analysis individually, or may use the specified data processor to support in the conduct of the analysis.
Expected Benefits:
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.
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.
Outputs:
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 Users of high cost activity
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from patient 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.
Processing:
The three Joint Data Controllers are NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG. Each CCG uses a separate data processor. The relevant relationships are:
NHS Bedfordshire CCG – South, Central and West Commissioning Support Unit
NHS Luton CCG – North East London Commissioning Support Unit
NHS Milton Keynes CCG – Arden and GEM Commissioning Support Unit
NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by NHS Oldham CCG) supply IT infrastructure for Arden and GEM Commissioning Support Unit and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Interxion, University Hospitals Bristol NHS Foundation Trust, Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
DATA MINIMISATION
Each CCG will receive data for their own geographical region. Data will be minimised for each CCG as follows:
• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where 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 CCG - this is only for commissioning and relates to both national and local flows.
NHS Digital will securely transfer the following minimised and pseudonymised datasets to the respective Commissioning Support Unit:
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)
Each Commissioning Support Unit link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
Each Commissioning Support Unit is only permitted to link data listed within this agreement. The pseudonymised data is then passed to the relevant CCG.
Patient level data may only be shared between the data controllers listed within the agreement and only be shared within the data controllers 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.
PROCESSING CONDITIONS
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from their relevant Data Controller and may only process data under instruction from the CCG which they have a processing agreement in place with:
NHS Bedfordshire CCG – South, Central and West Commissioning Support Unit
NHS Luton CCG – North East London Commissioning Support Unit
NHS Milton Keynes CCG – Arden and GEM Commissioning Support Unit
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.
Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
ONWARD SHARING:
Patient level data will not be shared outside of the data controllers. Re-identification of data is not permitted under this agreement.
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.
All access to data is auditable by NHS Digital.
DSfC - NHS Milton Keynes CCG - RS — DARS-NIC-294304-Q1M0X
Type of data: information not disclosed for TRE projects
Opt outs honoured: Yes - patient objections upheld, Identifiable (Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 s261(7)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Non Sensitive, and Non-Sensitive
When:DSA runs 2019-06-01 — 2022-05-31 2019.07 — 2021.03.
Access method: Frequent Adhoc Flow, One-Off
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- SUS for Commissioners
Objectives:
Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Limited
Expected Benefits:
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.
Outputs:
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.
Processing:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role.
Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the 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).
The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.
Onward Sharing
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.
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.
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 Risk Stratification:
• Patients who are normally registered and/or resident within NHS Milton Keynes CCG (including historical activity where the patient was previously registered or resident in another commissioner
The Bunker Secure Hosting Ltd do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
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 Prescribing Services Ltd, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data
processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
DSfC - NHS Bedfordshire CCG - RS — DARS-NIC-294268-B3Q6J
Type of data: information not disclosed for TRE projects
Opt outs honoured: Yes - patient objections upheld, Identifiable (Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 s261(7)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Non Sensitive, and Non-Sensitive
When:DSA runs 2019-06-01 — 2022-05-31 2019.06 — 2021.03.
Access method: Frequent Adhoc Flow, One-Off
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- SUS for Commissioners
Objectives:
Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by Prescribing Services Limited
Expected Benefits:
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.
Outputs:
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. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level.
4. 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.
5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to:
o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost
o Plan work for commissioning services and contracts
o Set up capitated budgets
o Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
Processing:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role.
Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the 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).
The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.
Onward Sharing
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.
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.
All access to data is auditable by NHS Digital.
Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.
Data Minimisation
Data Minimisation in relation to the data sets listed within the application are listed below. This also includes the purpose on which they would be applied -
For the purpose of Risk Stratification:
• Patients who are normally registered and/or resident within NHS Bedfordshire CCG (including historical activity where the patient was previously registered or resident in another commissioner).
The Bunker Secure Hosting Ltd do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
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
Prescribing Services Ltd, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
GDPPR COVID-19 CCG - Pseudo — DARS-NIC-416308-H6X4N
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent)
Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2020-11-18 — 2021-03-31 2021.01 — 2021.02.
Access method: One-Off, Frequent Adhoc Flow
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- GPES Data for Pandemic Planning and Research (COVID-19)
- COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
Objectives:
NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals.
GPES data for pandemic planning and research (GDPPR COVID 19)
To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the COVID-19 Directions.
The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patient’s GP record, such as details of:
• diagnoses and findings
• medications and other prescribed items
• investigations, tests and results
• treatments and outcomes
• vaccinations and immunisations
Details of any sensitive SNOMED codes included in the GDPPR data set can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data.
There are no free text record entries in the data.
The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes.
Such uses of the data include but are not limited to:
• Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact and to estimate when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions.
• Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified.
• Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions:
The data may only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data.
The linked data may only be used for purposes stipulated within this agreement and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. Reidentification of individuals is not permitted under this DSA.
LEGAL BASIS FOR PROCESSING DATA:
Legal Basis for NHS Digital to Disseminate the Data:
NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice).
The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI.
Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes.
Legal Basis for Processing:
The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2).
The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information:
Health organisations
“Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area
The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include:
• persons employed or engaged for the purposes of the health service
Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population.
Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures.
Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.
Expected Benefits:
• Manage demand and capacity
• Reallocation of resources
• Bring in additional workforce support
• Assists commissioners to make better decisions to support patients
• Identifying COVID-19 trends and risks to public health
• Enables CCGs to provide guidance and develop policies to respond to the outbreak
• Controlling and helping to prevent the spread of the virus
Outputs:
• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients due to the impact of COVID-19
• Analysis of resource allocation
• Investigating and monitoring the effects of COVID-19
• Patient Stratification in relation to COVID-19, such as:
o Patients at highest risk of admission
o Frail and elderly
o Patients that are currently in hospital
o Patients with prescriptions related to COVID-19
o Patients recently Discharged from hospital
For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.
Processing:
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
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.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).
The Recipients will take all required security measures to protect the disseminated data and they will not generate copies of their cuts of the disseminated data unless this is strictly necessary. Where this is necessary, the Recipients will keep a log of all copies of the disseminated data and who is controlling them and ensure these are updated and destroyed securely.
Onward sharing of patient level data is not permitted under this agreement. Only aggregated reports with small number suppression can be shared externally.
The data disseminated will only be used for COVID-19 GDPPR purposes as described in this DSA, any other purpose is excluded.
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.
AUDIT
All access to data is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms.
Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI.
DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below:
• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner area).
and/or
• Patients treated by a provider where the CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the CCG.
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
- GDPPR COVID 19 Data
Pseudonymisation is completed within the DSCRO and is then disseminated as follows:
1. Pseudonymised GDPPR COVID 19 data is securely transferred from the DSCRO to the Data Controller / Processor
2. Aggregation of required data will be completed by the Controller (or the Processor as instructed by the Controller).
3. Patient level data may not be shared by the Controller (or any of its processors).
GDPPR COVID-19 CCG - Pseudo — DARS-NIC-399787-Z7T4V
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent)
Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2020-09-01 — 2021-03-31 2021.01 — 2021.02.
Access method: One-Off, Frequent Adhoc Flow
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- GPES Data for Pandemic Planning and Research (COVID-19)
- COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
Objectives:
NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals.
GPES data for pandemic planning and research (GDPPR COVID 19)
To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the COVID-19 Directions.
The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patient’s GP record, such as details of:
• diagnoses and findings
• medications and other prescribed items
• investigations, tests and results
• treatments and outcomes
• vaccinations and immunisations
Details of any sensitive SNOMED codes included in the GDPPR data set can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data.
There are no free text record entries in the data.
The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes.
Such uses of the data include but are not limited to:
• Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact and to estimate when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions.
• Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified.
• Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions:
The data may only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data.
The linked data may only be used for purposes stipulated within this agreement and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. Reidentification of individuals is not permitted under this DSA.
LEGAL BASIS FOR PROCESSING DATA:
Legal Basis for NHS Digital to Disseminate the Data:
NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice).
The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI.
Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes.
Legal Basis for Processing:
The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2).
The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information:
Health organisations
“Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area
The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include:
• persons employed or engaged for the purposes of the health service
Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population.
Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures.
Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.
Expected Benefits:
• Manage demand and capacity
• Reallocation of resources
• Bring in additional workforce support
• Assists commissioners to make better decisions to support patients
• Identifying COVID-19 trends and risks to public health
• Enables CCGs to provide guidance and develop policies to respond to the outbreak
• Controlling and helping to prevent the spread of the virus
Outputs:
• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients due to the impact of COVID-19
• Analysis of resource allocation
• Investigating and monitoring the effects of COVID-19
• Patient Stratification in relation to COVID-19, such as:
o Patients at highest risk of admission
o Frail and elderly
o Patients that are currently in hospital
o Patients with prescriptions related to COVID-19
o Patients recently Discharged from hospital
For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.
Processing:
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
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.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).
The Recipients will take all required security measures to protect the disseminated data and they will not generate copies of their cuts of the disseminated data unless this is strictly necessary. Where this is necessary, the Recipients will keep a log of all copies of the disseminated data and who is controlling them and ensure these are updated and destroyed securely.
Onward sharing of patient level data is not permitted under this agreement. Only aggregated reports with small number suppression can be shared externally.
The data disseminated will only be used for COVID-19 GDPPR purposes as described in this DSA, any other purpose is excluded.
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.
AUDIT
All access to data is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms.
Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI.
DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below:
• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner area).
and/or
• Patients treated by a provider where the CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the CCG.
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
- GDPPR COVID 19 Data
Pseudonymisation is completed within the DSCRO and is then disseminated as follows:
1. Pseudonymised GDPPR COVID 19 data is securely transferred from the DSCRO to the Data Controller / Processor
2. Aggregation of required data will be completed by the Controller (or the Processor as instructed by the Controller).
3. Patient level data may not be shared by the Controller (or any of its processors).
GDPPR COVID-19 CCG - Pseudo — DARS-NIC-392341-F3R0B
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent)
Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2020-08-17 — 2021-03-31 2021.01 — 2021.02.
Access method: One-Off, Frequent Adhoc Flow
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- GPES Data for Pandemic Planning and Research (COVID-19)
- COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)
Objectives:
NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals.
GPES data for pandemic planning and research (GDPPR COVID 19)
To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the COVID-19 Directions.
The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patient’s GP record, such as details of:
• diagnoses and findings
• medications and other prescribed items
• investigations, tests and results
• treatments and outcomes
• vaccinations and immunisations
Details of any sensitive SNOMED codes included in the GDPPR data set can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data.
There are no free text record entries in the data.
The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes.
Such uses of the data include but are not limited to:
• Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact and to estimate when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions.
• Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified.
• Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions:
The data may only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data.
The linked data may only be used for purposes stipulated within this agreement and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. Reidentification of individuals is not permitted under this DSA.
LEGAL BASIS FOR PROCESSING DATA:
Legal Basis for NHS Digital to Disseminate the Data:
NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice).
The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI.
Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes.
Legal Basis for Processing:
The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2).
The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information:
Health organisations
“Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area
The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include:
• persons employed or engaged for the purposes of the health service
Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population.
Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures.
Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.
Expected Benefits:
• Manage demand and capacity
• Reallocation of resources
• Bring in additional workforce support
• Assists commissioners to make better decisions to support patients
• Identifying COVID-19 trends and risks to public health
• Enables CCGs to provide guidance and develop policies to respond to the outbreak
• Controlling and helping to prevent the spread of the virus
Outputs:
• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients due to the impact of COVID-19
• Analysis of resource allocation
• Investigating and monitoring the effects of COVID-19
• Patient Stratification in relation to COVID-19, such as:
o Patients at highest risk of admission
o Frail and elderly
o Patients that are currently in hospital
o Patients with prescriptions related to COVID-19
o Patients recently Discharged from hospital
For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.
Processing:
PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.
Data Processors must only act upon specific instructions from the Data Controller.
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.
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).
The Recipients will take all required security measures to protect the disseminated data and they will not generate copies of their cuts of the disseminated data unless this is strictly necessary. Where this is necessary, the Recipients will keep a log of all copies of the disseminated data and who is controlling them and ensure these are updated and destroyed securely.
Onward sharing of patient level data is not permitted under this agreement. Only aggregated reports with small number suppression can be shared externally.
The data disseminated will only be used for COVID-19 GDPPR purposes as described in this DSA, any other purpose is excluded.
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.
AUDIT
All access to data is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms.
Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI.
DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below:
• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner area).
and/or
• Patients treated by a provider where the CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the CCG.
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
- GDPPR COVID 19 Data
Pseudonymisation is completed within the DSCRO and is then disseminated as follows:
1. Pseudonymised GDPPR COVID 19 data is securely transferred from the DSCRO to the Data Controller / Processor
2. Aggregation of required data will be completed by the Controller (or the Processor as instructed by the Controller).
3. Patient level data may not be shared by the Controller (or any of its processors).
DSfC - NHS Milton Keynes CCG - Comm — DARS-NIC-178123-C4W3G
Type of data: information not disclosed for TRE projects
Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Section 251, Does not include the flow of confidential data)
Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(2)(b)(ii)
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive
When:DSA runs 2019-04-26 — 2020-04-25 2018.06 — 2020.03.
Access method: Frequent adhoc flow, Frequent Adhoc Flow
Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y
Sublicensing allowed: No
Datasets:
- Acute-Local Provider Flows
- Ambulance-Local Provider Flows
- Children and Young People Health
- Community-Local Provider Flows
- Demand for Service-Local Provider Flows
- Diagnostic Imaging Dataset
- Diagnostic Services-Local Provider Flows
- Emergency Care-Local Provider Flows
- Experience, Quality and Outcomes-Local Provider Flows
- Improving Access to Psychological Therapies Data Set
- Maternity Services Data Set
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- Mental Health-Local Provider Flows
- National Cancer Waiting Times Monitoring DataSet (CWT)
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Population Data-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Public Health and Screening Services-Local Provider Flows
- SUS for Commissioners
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Improving Access to Psychological Therapies Data Set_v1.5
- Diagnostic Imaging Data Set (DID)
- Improving Access to Psychological Therapies (IAPT) v1.5
- Mental Health and Learning Disabilities Data Set (MHLDDS)
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Services Data Set (MHSDS)
Objectives:
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)
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
§ 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
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The 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 Optum Health Solutions Limited
NHS Milton Keynes CCG is working collaboratively with hospital, community, mental health, ambulance, social care and General Practice health and care providers. Optum Health Solutions Limited will undertake an analytics project which will provide a foundation for integration work across the health and care system. It will introduce patient centric population health insight into the Milton Keynes health and care system. The Bedfordshire, Luton and Milton Keynes STP has signalled its intention to move towards an integrated care system and is an NHS England accelerator site. The population health analytics will provide a foundation for integration work across the system, however at this point is only within Milton Keynes.
Analysis of the linked datasets will present a joined up and comprehensive view of how patient cohorts interact with services across the Milton Keynes health and care system. It will be used to identify and understand priority population segments which clinical and system leaders will design future new care models around. This analytical process will engage leaders, clinicians and managers with how patients accessing their part of the system interact with other providers and services and will provide new insight into care model design. Commissioners and providers will use this insight to identify both short and long-term savings opportunities by identifying unwarranted variation in outcomes and service utilisation between population segments. The analysis outputs will be aggregate with small number suppression applied in line with NHS Digital standards.
Yielded Benefits:
Commissioning 1. Insights delivered to MK CCG on population needs, including locality specific information and benchmarking versus regional rates. Specific growth drivers within the population identified and quantified, and insights into high-cost segments of the population delivered. 2. Local providers engaged in conversations around high-cost segments, including how local services are shaped to deliver to these segments. Multiple on-site workshops held with local clinicians and provider management, and insights delivered on specific local needs. 3. Significant clinical engagement in analytics outcomes and further avenues of enquiry explored, and change in clinical behaviour in response to insights has been noted. Further analytical work is required to embed these approaches systematically. 4. Significant capability coaching of local leaders, analysts and clinicians has been undertaken off the back of the work done with this data, and local knowledge of pop health management has increased. Further analytical work is required to embed these approaches systematically. 5. As part of local provider and local authority engagement, integrated care has been the cornerstone of the analytics done to date, and the insights delivered have enabled discussions from across health and social care.
Expected Benefits:
Commissioning
1. Insight into the health needs of the population and how they are changing – the population health analytics will analyse how changes in the population are diving growth in service utilisation across the system.
2. Insight into how well services are aligned to the health needs of the population – the analytics will consider current service delivery and whether it Is optimised for effective population health management.
3. Insight into unwarranted variation in clinical and economic outcomes between population segments (opportunity identification) – the analytics will highlight high levels of variation in cost and utilisation between population groups, these will be clinically validated and fed back into the planning system as potential savings opportunities.
4. Supporting the development of population health management.
5. Supporting the development of integrated care.
Outputs:
Commissioning
1. Linked data quality report – this report will be used to work with data specialists within Milton Keynes to validate the data used against a local view, this will ensure the data is accurate and representative.
2. Initial analytical review of the data for feedback from MK analytics specialists – this report will be used to test and validate insights from Optums analysis with local NHS analytical experts.
3. Initial analytical review of the data for clinical engagement and feedback – this report will be used to validate whether variation in service utilisation between different groups of patients is considered normal by clinicians.
4. Final analytical review for analytical and clinical stakeholders – this report will summarise the key findings from the initial analytical reviews. It also will include analysis on any additional lines of enquiry based on feedback from the initial analytical reviews.
5. Final report for Milton Keynes CCG, Local Authority and GP practices – this report will present the findings of the project to stakeholders across the system. It will include all the key insights and in some cases may include recommendations for new clinical models or advice on population health management strategies, these will be aligned to priority population groups and designed to address unwarranted variation in health outcomes.
Notes on Outputs
• The five reports will only contain aggregate data with small number suppression.
• No record level, patient level or event level data will be shared outside of Optums secure environment.
• All data handled by Optum will be pseudonymised at all times and Optum will not have access to the decryption key.
• Any additional reporting requested by the CCG will be prepared in either an anonymised or aggregate format and will not be shared outside of the CCG unless it is aggregate with small number suppression.
Processing:
Data must only be used as stipulated within this Data Sharing Agreement.
Data Processors must only act upon specific instructions from the Data Controller.
Data can only be stored at the addresses listed under storage addresses.
The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG.
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.
All access to data is managed under Roles-Based Access Controls
No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality and that data required by the applicant.
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)
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.
All access to data is auditable by NHS Digital.
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)
Data quality management and pseudonymisation is completed within the DSCRO. Pseudonymisation is undertaken using the Medeanalytics pseudonymisation at source tool. The DSCRO will generate a salt encryption key to be used for this project and will share it with Milton Keynes Council and Apollo Medical (who will be acting as a Data Processor for the GPs) Data is then disseminated as follows:
Data Processor – Optum Health Solutions Limited
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) and National Cancer Waiting Times Monitoring Data Set (CWT) only is securely transferred from the DSCRO to Optum Health Solutions Limited.
2. Optum Health Solutions Limited Solutions will receive pseudonymised primary care data from the Milton Keynes General Practices, via their data processor Apollo, using secure FTP. The data is pseudonymised before leaving the GP system.
3. Milton Keynes Council pseudonymise Social Care data using the MedeAnalytics pseudonymisation at source tool. Milton Keynes Council then send pseudonymised Social Care data to Optum Health Solutions Limited
4. Optum Health Solutions Limited add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Undertake population health management
c. Undertake data quality and validation checks
d. Thoroughly investigate the needs of the population
e. Understand cohorts of residents who are at risk
f. Conduct Health Needs Assessments
5. Allowed linkage is between the data sets contained within points 1, 2 and 3.
6. Aggregation of required data for CCG management use will be completed by Optum Health Solutions Limited or the CCG as instructed by the CCG.
7. Aggregated reports with small number suppression will be sent to the CCG.
8. 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.
No data is sent to, processed or stored by MedeAnalytics.
Optum Health Solutions Limited will not reidentify any data.