NHS Digital Data Release Register - reformatted
NHS South West London ICB - 36l projects
- GDPPR COVID-19 CCG - Pseudo
- DSfC - NHS South West London CCG - RS & Comms
- DSfC - NHS Croydon CCG - STP - Comm
- DSfC - NHS Richmond CCG - RS
- DSfC - NHS Kingston CCG - RS
- DSfC - NHS Croydon CCG - RS
406 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
GDPPR COVID-19 CCG - Pseudo — NIC-399808-H3X8Q
Opt outs honoured: No - Statutory exemption to flow confidential data without consent (Excuses: 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 – 2021-03 2021.01 — 2021.05.
Access method: One-Off, Frequent Adhoc Flow
Data-controller type: NHS SOUTH WEST LONDON CCG, NHS SOUTH WEST LONDON ICB - 36L
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)
Type of data: Anonymised - ICO Code Compliant
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 South West London CCG - RS & Comms — NIC-362239-F6V0N
Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld (Excuses: 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 - '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 2020-04 – 2023-03 2020.04 — 2021.05.
Access method: Frequent Adhoc Flow, One-Off
Data-controller type: NHS SOUTH WEST LONDON CCG, NHS SOUTH WEST LONDON ICB - 36L
Sublicensing allowed: No
AGD/predecessor discussions: IGARD Minutes - 1 July 2021 Final.pdf
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
- e-Referral Service for Commissioning
- Personal Demographic Service
- Summary Hospital-level Mortality Indicator
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
- Medicines dispensed in Primary Care (NHSBSA data)
- 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)
Type of data: Anonymised - ICO Code Compliant, Identifiable
Objectives:
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 Sollis Partnership Ltd.
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
- Civil Registries Data (CRD) (Births and Deaths)
The pseudonymised data is required to for the following purposes:
Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
Data Quality and Validation – allowing data quality checks on the submitted data
Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
Service redesign
Health Needs Assessment – identification of underlying disease prevalence within the local population
Patient stratification and predictive modelling - to highlight patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models
The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North East London Commissioning Support Unit
Expected 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
6. healthcare outcomes.
All of the above lead to improved patient experience through more effective commissioning of services
Commissioning
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
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:
Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.
COMMISSIONING
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include high flyers.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where 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.
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 Type 2 objections before any identifiable data leaves the DSCRO.
CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.
(RS) The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.
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 South West London CCG (including historical activity where the patient was previously registered or resident in another commissioner
For the purpose of Commissioning:
• Patients who are normally registered and/or resident within the CCG (including historical activity where the patient was previously registered or resident in another commissioner).
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 – 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 CCG - this is only for commissioning and relates to both national and local flows.
Microsoft UK supply provide Cloud Services and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.
Interxion UK 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 - The Sollis Partnership Ltd
1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to the NHS North and East London Commissioning Support Unit where the data is landed and then securely passed onto The Sollis Partnership Ltd. The Sollis Partnership Ltd holds the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to NHS North and East London CSU.
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 The Sollis Partnership 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 and Deaths)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – North East London Commissioning Support Unit
1) Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North East London Commissioning Support Unit.
2) North East London Commissioning Support Unit add derived fields, link data and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning.
o Check recorded activity against contracts or invoices and facilitate discussions with providers.
o Undertake population health management
o Undertake data quality and validation checks
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
3) Allowed linkage is between the data sets contained within point 1.
4) North East London Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG.
5) Aggregation of required data for CCG management use will be completed by North East London Commissioning 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.
DSfC - NHS Croydon CCG - STP - Comm — NIC-161143-S2S3Z
Opt outs honoured: No - data flow is not identifiable (Excuses: 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 – 2022-04 2018.06 — 2020.03.
Access method: Frequent adhoc flow, Frequent Adhoc Flow
Data-controller type: NHS SOUTH WEST LONDON CCG, NHS SOUTH WEST LONDON ICB - 36L
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 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)
Type of data: Anonymised - ICO Code Compliant
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
• Ensuring we do what we should
§ 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.
The legal basis is as follows:
For dissemination
- Section 261(1) of Health and Social Care Act 2012
- Section 261(2)(b)(ii) of Health and Social Care Act 2012
-
GDPR:
- Article 6(1)(e)
- Article 9(2)(h)
- Article 9(3)
- Section 11 Data Protection Act 2018
Processing for commissioning will be conducted by North East London Commissioning Support Unit
Yielded Benefits:
Expected Benefits:
Commissioning
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
Outputs:
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 audited
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. 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 East London Commissioning Support Unit
1) Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times Monitoring Data Set (CWT) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North East London Commissioning Support Unit.
2) North East London Commissioning Support Unit add derived fields, link data and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning.
o Check recorded activity against contracts or invoices and facilitate discussions with providers.
o Undertake population health management
o Undertake data quality and validation checks
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
3) Allowed linkage is between the data sets contained within point 1.
4) North East London Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG.
5) Aggregation of required data for CCG management use will be completed by North East London Commissioning 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.
DSfC - NHS Richmond CCG - RS — NIC-43547-B4R5Q
Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld (Excuses: Section 251, Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data, 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); National Health Service Act 2006 - s251 - 'Control of patient information'.
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive
When:DSA runs 2019-07 – 2022-07 2017.06 — 2017.05.
Access method: Ongoing, Frequent adhoc flow, Frequent Adhoc Flow
Data-controller type: NHS SOUTH WEST LONDON CCG, NHS SOUTH WEST LONDON ICB - 36L
Sublicensing allowed: No
AGD/predecessor discussions: igard_minutes_14_december_2017.pdf, IGARD Minutes - 26 January 2023 final.pdf, IGARD Minutes - 16 December 2021 final.pdf, IGARD Minutes - 23 September 2021 final.pdf, IGARD Minutes - 26 August 2021 final.pdf, IGARD Minutes - 19 August 2021 FINAL.pdf, IGARD Minutes - 5th August 2021 final.pdf, IGARD Minutes - 29 July 2021 - FINAL.pdf, IGARD Minutes - 27th May 2021 final.pdf, igard-minutes---6-aug-2020-final.pdf, IGARD_Minutes_11_January_2018.pdf, igardminutes-21stjanuary2021final.pdf, igardminutes-14thjanuary2021final.pdf
Datasets:
- Children and Young People's Health Services Data Set
- Improving Access to Psychological Therapies Data Set
- Local Provider Data - Acute
- Local Provider Data - Ambulance
- Local Provider Data - Community
- Local Provider Data - Demand for Service
- Local Provider Data - Diagnostic Services
- Local Provider Data - Emergency Care
- Local Provider Data - Experience Quality and Outcomes
- Local Provider Data - Public Health & Screening services
- Local Provider Data - Mental Health
- Local Provider Data - Population Data
- Local Provider Data - Primary Care
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- SUS Accident & Emergency data
- SUS Admitted Patient Care data
- SUS Outpatient data
- Local Provider Data - Other not elsewhere classified
- Maternity Services Dataset
- SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
- SUS for Commissioners
- Public Health and Screening Services-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Population Data-Local Provider Flows
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Mental Health-Local Provider Flows
- Maternity Services Data Set
- Experience, Quality and Outcomes-Local Provider Flows
- Emergency Care-Local Provider Flows
- Diagnostic Services-Local Provider Flows
- Diagnostic Imaging Dataset
- Demand for Service-Local Provider Flows
- Community-Local Provider Flows
- Children and Young People Health
- Ambulance-Local Provider Flows
- Acute-Local Provider Flows
- SUS (Accident & Emergency, Inpatient and Outpatient data)
- Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Population Data, Primary Care, Public Health & Screening services
Type of data: Identifiable
Objectives:
Risk Stratification
This is an application to use SUS data identifiable at the level of NHS number for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users.
Pseudonymised – SUS and Local Flows
Application for the CCG 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.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs 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.
No record level data will be linked other than as specifically detailed within this application/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 of interest of the applicant.
Yielded Benefits:
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 and early intervention of appropriate care.
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. 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.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.
Pseudonymised – SUS and Local Flows
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.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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.
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:
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. 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 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.
Pseudonymised – SUS and Local Flows
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.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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:
South London DSCRO (part of NHS Digital) will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO.
Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository to South London Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by South London DSCRO and the data identifiable at the level of NHS number is transferred securely to South East CSU, who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to South East CSU.
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. South East CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once South East CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.
Pseudonymised – SUS and Local Flows
Data Processor 1 (South East CSU)
1. South London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. South London DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to South East CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows
3. South East CSU 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.
4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG.
5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.
Data Processor 2 (South, Central and West CSU)
1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. South Collaborative DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows
3. South Central and West CSU 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.
4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG.
5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.
Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
Data Processor 1 (South East CSU)
1. South London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to South East CSU for the addition of derived fields and analysis.
3. South East CSU then pass the processed, pseudonymised data to the CCG.
4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5. Aggregation of required data for CCG management use will be completed by the 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 where contractual arrangements are in place.
Data Processor 2 (South, Central and West CSU)
1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields and analysis.
3. South Central and West CSU then pass the processed, pseudonymised data to the CCG.
4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5. Aggregation of required data for CCG management use will be completed by the 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 where contractual arrangements are in place.
DSfC - NHS Kingston CCG - RS — NIC-43450-C7M7C
Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld (Excuses: Section 251, Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data, 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(7); National Health Service Act 2006 - s251 - 'Control of patient information'.
Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)
Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive
When:DSA runs 2019-07 – 2022-07 2017.06 — 2017.05.
Access method: Ongoing, Frequent adhoc flow, Frequent Adhoc Flow
Data-controller type: NHS SOUTH WEST LONDON CCG, NHS SOUTH WEST LONDON ICB - 36L
Sublicensing allowed: No
AGD/predecessor discussions: igard_minutes_14_december_2017.pdf, IGARD Minutes - 26 January 2023 final.pdf, IGARD Minutes - 16 December 2021 final.pdf, IGARD Minutes - 23 September 2021 final.pdf, IGARD Minutes - 26 August 2021 final.pdf, IGARD Minutes - 19 August 2021 FINAL.pdf, IGARD Minutes - 5th August 2021 final.pdf, IGARD Minutes - 29 July 2021 - FINAL.pdf, IGARD Minutes - 27th May 2021 final.pdf, igard-minutes---6-aug-2020-final.pdf, IGARD_Minutes_11_January_2018.pdf, igardminutes-21stjanuary2021final.pdf, igardminutes-14thjanuary2021final.pdf
Datasets:
- Children and Young People's Health Services Data Set
- Improving Access to Psychological Therapies Data Set
- Local Provider Data - Acute
- Local Provider Data - Ambulance
- Local Provider Data - Community
- Local Provider Data - Demand for Service
- Local Provider Data - Diagnostic Services
- Local Provider Data - Emergency Care
- Local Provider Data - Experience Quality and Outcomes
- Local Provider Data - Public Health & Screening services
- Local Provider Data - Mental Health
- Local Provider Data - Population Data
- Local Provider Data - Primary Care
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- SUS Accident & Emergency data
- SUS Admitted Patient Care data
- SUS Outpatient data
- Local Provider Data - Other not elsewhere classified
- Maternity Services Dataset
- SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
- SUS for Commissioners
- Public Health and Screening Services-Local Provider Flows
- Primary Care Services-Local Provider Flows
- Population Data-Local Provider Flows
- Other Not Elsewhere Classified (NEC)-Local Provider Flows
- Mental Health-Local Provider Flows
- Maternity Services Data Set
- Experience, Quality and Outcomes-Local Provider Flows
- Emergency Care-Local Provider Flows
- Diagnostic Services-Local Provider Flows
- Diagnostic Imaging Dataset
- Demand for Service-Local Provider Flows
- Community-Local Provider Flows
- Children and Young People Health
- Ambulance-Local Provider Flows
- Acute-Local Provider Flows
- SUS (Accident & Emergency, Inpatient and Outpatient data)
- Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Population Data, Primary Care, Public Health & Screening services
Type of data: Identifiable
Objectives:
ASH Status
This is an application to use SUS data identifiable at the level of NHS Number and local provider data identifiable at the level of NHS Number according to S.251 CAG 2-03(a)/2013.
The NHS number 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 analysis of patient data across health pathways.
The application also includes a request for MHSDS, MHMDS, MHLDDS and MSDS data identifiable at the level of NHS number to provide intelligence to support commissioning of health services.
Risk Stratification
This is an application to use SUS data identifiable at the level of NHS number for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users.
Pseudonymised – SUS and Local Flows
This is an application for the CCG to use pseudonymised SUS and local provider data to provide intelligence to support commissioning of health services. The linked, 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.
Pseudonymised – IAPT, CYPHS and DIDS
This is an application for the CCG to use IAPT, CYPHS and DIDs 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.
No record level data will be linked other than as specifically detailed within this application/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 the HSCIC will not be national data, but only that data relating to the specific locality of interest of the applicant.
Yielded Benefits:
Expected Benefits:
ASH Status
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.
(b) 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) flows.
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. .
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 and early intervention of appropriate care.
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) 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.
5) Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.
Pseudonymised – IAPT, CYPHS and DIDS
1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways.
2) Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3) Health economic modelling using:
(a) Analysis on provider performance.
(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.
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:
ASH Status
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.
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. 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 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.
ASH – SUS and Local Flows
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.
Pseudonymised – IAPT, CYPHS and DIDS
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.
Processing:
South London DSCRO will apply Type 2 objections (from 1st October 2016 onwards) before any identifiable data leaves the DSCRO.
ASH Status
For the purpose of commissioning activities, the CCG requires SUS data identifiable at the level of NHS Number. The CCG also requires local provider data identifiable at the level of NHS number.
South East CSU acts as the data processor on behalf of the CCG, receiving SUS and local provider data identifiable at the level of NHS number.
South London DSCRO has a legitimate relationship with the CCG, for the provision of data.
1. a) South London DSCRO– part of the HSCIC - receive identifiable SUS data from the SUS Repository at HSCIC. DSCRO also receives identifiable local provider data directly from Providers (as per Data Services for Commissioners Directions 2015).
b) South London DSCRO also receives MHMDS, MHSDS, MHLDDS and MSDS data with NHS number.
2. Data quality management and standardisation of the data is completed by South London DSCRO.
3. a) South London DSCRO then securely transfers the SUS data identifiable at the level of NHS number and Local Provider data identifiable at the level of NHS number to South East CSU.
4. South London DSCRO then securely transfers the MHMDS, MHSDS, MHLDDS and MSDS data identifiable at the level of NHS number to South East CSU.
5. South East CSU ensures the addition of derived fields and analysis takes place, including linkage of SUS and local provider data, then flows the data securely to the CCG.
Risk Stratification
1) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from South London Data Services for Commissioners Regional Office (DSCRO) to the data processor.
2) Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to South East CSU, who hold the SUS data within the secure Data Centre on N3.
3) SUS data is linked to GP data in the risk stratification tool by the data processor.
4) 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.
5) South East CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
6) Once South East CSU has completed the processing, the CCG can dial into the online system via N3 connection to access the data anonymised at patient level.
Pseudonymised – IAPT, CYPHS and DIDS
1) South London Data Services for Commissioners Regional Office (DSCRO) receive a flow of pseudonymised patient level data for each CCG for Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes
2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to South East CSU for the addition of derived fields and analysis.
3) South East CSU then pass the processed, pseudonymised data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level.
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 in line with the HES analysis guide.
DSfC - NHS Croydon CCG - RS — NIC-43431-N0G4J
Opt outs honoured: N, Yes - patient objections upheld (Excuses: Section 251, Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012, 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(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 2019-07 – 2022-07 2017.06 — 2017.05.
Access method: Ongoing, Frequent adhoc flow, Frequent Adhoc Flow
Data-controller type: NHS SOUTH WEST LONDON CCG, NHS SOUTH WEST LONDON ICB - 36L
Sublicensing allowed: No
AGD/predecessor discussions: igard_minutes_14_december_2017.pdf, IGARD Minutes - 26 January 2023 final.pdf, IGARD Minutes - 16 December 2021 final.pdf, IGARD Minutes - 23 September 2021 final.pdf, IGARD Minutes - 26 August 2021 final.pdf, IGARD Minutes - 19 August 2021 FINAL.pdf, IGARD Minutes - 5th August 2021 final.pdf, IGARD Minutes - 29 July 2021 - FINAL.pdf, IGARD Minutes - 27th May 2021 final.pdf, igard-minutes---6-aug-2020-final.pdf, IGARD_Minutes_11_January_2018.pdf, igardminutes-21stjanuary2021final.pdf, igardminutes-14thjanuary2021final.pdf
Datasets:
- Children and Young People's Health Services Data Set
- Improving Access to Psychological Therapies Data Set
- Local Provider Data - Acute
- Local Provider Data - Ambulance
- Local Provider Data - Community
- Local Provider Data - Demand for Service
- Local Provider Data - Diagnostic Services
- Local Provider Data - Emergency Care
- Local Provider Data - Experience Quality and Outcomes
- Local Provider Data - Public Health & Screening services
- Local Provider Data - Mental Health
- Local Provider Data - Population Data
- Local Provider Data - Primary Care
- Mental Health and Learning Disabilities Data Set
- Mental Health Minimum Data Set
- Mental Health Services Data Set
- SUS Accident & Emergency data
- SUS Admitted Patient Care data
- SUS Outpatient data
- Local Provider Data - Other not elsewhere classified
- Maternity Services Dataset
- SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
- SUS for Commissioners
- SUS (Accident & Emergency, Inpatient and Outpatient data)
- Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Population Data, Primary Care, Public Health & Screening services
Type of data: Identifiable
Objectives:
Risk Stratification
This is an application to use SUS data identifiable at the level of NHS number for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users.
Pseudonymised – SUS and Local Flows
Application for the CCG 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.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs 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.
No record level data will be linked other than as specifically detailed within this application/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 of interest of the applicant.
Yielded Benefits:
n/a
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 and early intervention of appropriate care.
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. 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.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.
Pseudonymised – SUS and Local Flows
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.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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.
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:
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. 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 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.
Pseudonymised – SUS and Local Flows
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.
Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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:
South London DSCRO (part of NHS Digital) will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO.
Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository to South London Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by South London DSCRO and the data identifiable at the level of NHS number is transferred securely to South East CSU, who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to South East CSU.
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. South East CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once South East CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.
Pseudonymised – SUS and Local Flows
Data Processor 1 (South East CSU)
1. South London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. South London DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to South East CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows
3. South East CSU 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.
4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG.
5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.
Data Processor 2 (South, Central and West CSU)
1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. South Collaborative DSCRO also obtains identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows
3. South Central and West CSU 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.
4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG.
5. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression in line with the HES analysis guide can be shared where contractual arrangements are in place.
Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
Data Processor 1 (South East CSU)
1. South London Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to South East CSU for the addition of derived fields and analysis.
3. South East CSU then pass the processed, pseudonymised data to the CCG.
4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5. Aggregation of required data for CCG management use will be completed by the 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 where contractual arrangements are in place.
Data Processor 2 (South, Central and West CSU)
1. South Collaborative Data Services for Commissioners Regional Office (DSCRO) obtains a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields and analysis.
3. South Central and West CSU then pass the processed, pseudonymised data to the CCG.
4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5. Aggregation of required data for CCG management use will be completed by the 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 where contractual arrangements are in place.