NHS Digital Data Release Register - reformatted

NHS Bedfordshire Ccg projects

DSfC - NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG - Comm
DSfC - NHS Bedfordshire CCG - RS
DSfC - NHS Bedfordshire CCG - IV & Comm
GDPPR COVID-19 CCG - Pseudo
Project 5

1392 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

🚩 NHS Bedfordshire Ccg was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Bedfordshire Ccg may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

DSfC - NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG - Comm — DARS-NIC-338789-M0T3Q

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(2)(b)(ii)

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)

Sensitive: Sensitive

When:DSA runs 2019-11-15 — 2022-11-14 2019.12 — 2021.03.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y

Sublicensing allowed: No

Datasets:

Acute-Local Provider Flows
Ambulance-Local Provider Flows
Children and Young People Health
Civil Registration - Births
Civil Registration - Deaths
Community Services Data Set
Community-Local Provider Flows
Demand for Service-Local Provider Flows
Diagnostic Imaging Dataset
Diagnostic Services-Local Provider Flows
Emergency Care-Local Provider Flows
Experience, Quality and Outcomes-Local Provider Flows
Improving Access to Psychological Therapies Data Set
Maternity Services Data Set
Mental Health and Learning Disabilities Data Set
Mental Health Minimum Data Set
Mental Health Services Data Set
Mental Health-Local Provider Flows
National Cancer Waiting Times Monitoring DataSet (CWT)
National Diabetes Audit
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Patient Reported Outcome Measures
Population Data-Local Provider Flows
Primary Care Services-Local Provider Flows
Public Health and Screening Services-Local Provider Flows
SUS for Commissioners
National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
Improving Access to Psychological Therapies Data Set_v1.5
Civil Registrations of Death
Community Services Data Set (CSDS)
Diagnostic Imaging Data Set (DID)
Improving Access to Psychological Therapies (IAPT) v1.5
Mental Health and Learning Disabilities Data Set (MHLDDS)
Mental Health Minimum Data Set (MHMDS)
Mental Health Services Data Set (MHSDS)
Patient Reported Outcome Measures (PROMs)

Objectives:

NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG work jointly across the region to fulfil their commissioning functions. The CCGs will work proactively and collaboratively with each other to redesign services across boundaries to integrate services.

The CCGs will use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the geographical region.

The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.

The pseudonymised data is required for the following purposes:
 Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
 Data Quality and Validation – allowing data quality checks on the submitted data
 Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
 Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
 Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
 Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
 Service redesign
 Health Needs Assessment – identification of underlying disease prevalence within the local population
 Patient stratification and predictive modelling - to highlight patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCGs area based on the full analysis of multiple pseudonymised datasets.

Data will be shared between the three joint data controllers. Rather than sharing full datasets, most of the time, it may be selected reports that will be shared. These reports will be at record level rather than aggregated with small number suppression. On occasions, the reports may include the data that sits behind the reports.

Working collaboratively, there may be occasions where one CCG takes the lead on specific region wide analysis, providing outcomes to the other two. The CCGs are able to conduct analysis individually, or may use the specified data processor to support in the conduct of the analysis.

Expected Benefits:

1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.

Outputs:

1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Users of high cost activity
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from patient stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.

Processing:

The three Joint Data Controllers are NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG. Each CCG uses a separate data processor. The relevant relationships are:

NHS Bedfordshire CCG – South, Central and West Commissioning Support Unit
NHS Luton CCG – North East London Commissioning Support Unit
NHS Milton Keynes CCG – Arden and GEM Commissioning Support Unit

NHS Midlands and Lancashire Commissioning Support Unit and Greater Manchester Shared Services (hosted by NHS Oldham CCG) supply IT infrastructure for Arden and GEM Commissioning Support Unit and are therefore listed as data processors. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Interxion, University Hospitals Bristol NHS Foundation Trust, Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

DATA MINIMISATION

Each CCG will receive data for their own geographical region. Data will be minimised for each CCG as follows:

• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of CCG - this is only for commissioning and relates to both national and local flows.

NHS Digital will securely transfer the following minimised and pseudonymised datasets to the respective Commissioning Support Unit:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
12. Civil Registries Data (CRD) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)

Each Commissioning Support Unit link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
Each Commissioning Support Unit is only permitted to link data listed within this agreement. The pseudonymised data is then passed to the relevant CCG.

Patient level data may only be shared between the data controllers listed within the agreement and only be shared within the data controllers on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

PROCESSING CONDITIONS
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.

Data Processors must only act upon specific instructions from their relevant Data Controller and may only process data under instruction from the CCG which they have a processing agreement in place with:
NHS Bedfordshire CCG – South, Central and West Commissioning Support Unit
NHS Luton CCG – North East London Commissioning Support Unit
NHS Milton Keynes CCG – Arden and GEM Commissioning Support Unit

Data can only be stored at the addresses listed under storage addresses.

All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)

ONWARD SHARING:
Patient level data will not be shared outside of the data controllers. Re-identification of data is not permitted under this agreement.
Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.

SEGREGATION:
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.

All access to data is auditable by NHS Digital.

DSfC - NHS Bedfordshire CCG - RS — DARS-NIC-294268-B3Q6J

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable (Section 251 NHS Act 2006)

Legal basis: Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 s261(7)

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)

Sensitive: Non Sensitive, and Non-Sensitive

When:DSA runs 2019-06-01 — 2022-05-31 2019.06 — 2021.03.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y

Sublicensing allowed: No

Datasets:

SUS for Commissioners

Objectives:

Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.

To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.

Risk Stratification will be conducted by Prescribing Services Limited

Expected Benefits:

Risk stratification promotes improved case management in primary care and will lead to the following benefits
being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing
commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify
priorities and identify plans to address these.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency
admissions. This is achieved through mapping of frequent users of emergency services thus allowing early
intervention.
3. Improved access to services by identifying which services may be in demand but have poor access, and from this
identify areas where improvement is required.
4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG
Outcome Framework by allowing for more targeted intervention in primary care.
5. Better understanding of local population characteristics through analysis of their health and healthcare
outcomes.
All of the above lead to improved patient experience through more effective commissioning of services.

Outputs:

1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level.
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to:
o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost
o Plan work for commissioning services and contracts
o Set up capitated budgets
o Identify health determinants of risk of admission to hospital, or other adverse care outcomes.

Processing:

Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.

Data Processors must only act upon specific instructions from the Data Controller.

Data can only be stored at the addresses listed under storage addresses.

All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data).

The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.

CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.

The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.

Onward Sharing

Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.

Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.

Segregation

Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.

All access to data is auditable by NHS Digital.

Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.

Data Minimisation
Data Minimisation in relation to the data sets listed within the application are listed below. This also includes the purpose on which they would be applied -

For the purpose of Risk Stratification:
• Patients who are normally registered and/or resident within NHS Bedfordshire CCG (including historical activity where the patient was previously registered or resident in another commissioner).

The Bunker Secure Hosting Ltd do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Risk Stratification
1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to
Prescribing Services Ltd, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.

DSfC - NHS Bedfordshire CCG - IV & Comm — DARS-NIC-49738-Q2B0D

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld, No - DSfC for Invoice Validation Purposes, Anonymised - ICO Code Compliant, Identifiable (Section 251, Section 251 NHS Act 2006, Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(7), Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 s261(2)(b)(ii)

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)

Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive

When:DSA runs 2018-12-01 — 2021-11-30 2018.06 — 2021.03.

Access method: Frequent adhoc flow, Frequent Adhoc Flow, One-Off

Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y

Sublicensing allowed: No

Datasets:

Acute-Local Provider Flows
Children and Young People Health
Community Services Data Set
Community-Local Provider Flows
Demand for Service-Local Provider Flows
Diagnostic Imaging Dataset
Diagnostic Services-Local Provider Flows
Emergency Care-Local Provider Flows
Experience, Quality and Outcomes-Local Provider Flows
Improving Access to Psychological Therapies Data Set
Maternity Services Data Set
Mental Health and Learning Disabilities Data Set
Mental Health Minimum Data Set
Mental Health Services Data Set
Mental Health-Local Provider Flows
National Cancer Waiting Times Monitoring DataSet (CWT)
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Population Data-Local Provider Flows
Primary Care Services-Local Provider Flows
Public Health and Screening Services-Local Provider Flows
Ambulance-Local Provider Flows
SUS for Commissioners
Civil Registration - Births
Civil Registration - Deaths
e-Referral Service for Commissioning
National Diabetes Audit
Patient Reported Outcome Measures
National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
Improving Access to Psychological Therapies Data Set_v1.5
Civil Registrations of Death
Community Services Data Set (CSDS)
Diagnostic Imaging Data Set (DID)
Improving Access to Psychological Therapies (IAPT) v1.5
Mental Health and Learning Disabilities Data Set (MHLDDS)
Mental Health Minimum Data Set (MHMDS)
Mental Health Services Data Set (MHSDS)
Patient Reported Outcome Measures (PROMs)

Objectives:

Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so they are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets and will not be used further.

Invoice Validation with be conducted by South Central & West Commissioning Support Unit
The CCG are advised by South Central & West Commissioning Support Unit whether payment for invoices can be made or not.

Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)
The pseudonymised data is required to for the following purposes:
§ Population health management:
• Understanding the interdependency of care services
• Targeting care more effectively
• Using value as the redesign principle
§ Data Quality and Validation – allowing data quality checks on the submitted data
§ Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them
§ Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs
§ Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated
§ Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another
§ Service redesign
§ Health Needs Assessment – identification of underlying disease prevalence within the local population
§ Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by North East London Commissioning Support Unit, Mede Analytics and South Central & West Commissioning Support Unit

National identifiers will be removed by NHS Digital (DSCRO) using MedeAnalytics’ Pseudonymisation at Source process, prior to data leaving NHS Digital. By using the MedeAnalytics process, the resulting de-identified data can be linked within the MedeAnalytics system with data from other providers (as specified in this application) using the same process, without the need for identifiable data to flow to MedeAnalytics .

Further, as national identifiers are removed by NHS Digital before transmission, thus together with other approaches rendering the data Anonymous in line with the ICO’s anonymisation code of practice, the resulting, non-identifiable data representing 100% of the commissioner’s records is suitable for General Commissioning and Contract Validation purposes, both of which have been previously approved. As data Is anonymous in context, there is no need to remove records for type 2 objectors, as the records are no longer identifiable when they leave the protected NHS Digital environment.

Where analysis of pseudonymised patient records show that the associated patients could benefit from clinical interventions, GP Practice users who have legitimate relationships with the patients will be able to re-identify the patient records so that they can provide the interventions (direct care).

Yielded Benefits:

The CCG has realised the measurable benefits for the data collection and the viable evaluation data has enabled services to be delivered to match the population requirements whilst planning for future needs. This work will continue year on year to match the delivery/funding of targets services for the population. The QIPP Project Management Office (PMO) is where we used the process to identify the activity within contracts at a detailed level and set phased plans to then monitor against in year. This saved the PMO team the labour resource of aggregating many reports as all QIPPs relating to acute contracts were within the one output from our process. This assisted the CCG to set, monitor and track progress of schemes in a timely way each month to assure itself that it could meet its transformation requirements and change the ways in which care was being delivered. In addition, this monitoring helps identify new areas of QIPP that can be targeted moving forward, thus quickly identifying areas of concern.

Expected Benefits:

Invoice Validation

1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Commissioning

1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.

Outputs:

Invoice Validation

1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Commissioning

1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports include high flyers.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o Most expensive patients (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community

Processing:

Processing activities:
Data must only be used as stipulated within this Data Sharing Agreement.

Data Processors must only act upon specific instructions from the Data Controller.

Data can only be stored at the addresses listed under storage addresses.

Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.

All access to data is managed under Roles-Based Access Controls

No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)

Segregation
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.

All access to data is auditable by NHS Digital.

Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.

Data Minimisation
Data Minimisation in relation to the data sets listed within section 3 are listed below. This also includes the purpose on which they would be applied -

For the purpose of Commissioning:
• Patients who are normally registered and/or resident within the commissioner (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where the commissioner is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the commissioner - this is only for commissioning and relates to both national and local flows.

For the purpose of Invoice Validation:
• CCG of residence and/or registration.

The above relates to data requested only (Table 3B). Data currently held (Table 3A) will have the following Data Minimisation:
• CCG of residence and/or registration.

For clarity, any access by Interxion to data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Invoice Validation
1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the South Central & West Commissioning Support Unit.
3. South Central & West Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between South Central & West Commissioning Support UnitCEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:

Commissioning
The North East London Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1) SUS
2) Local Provider Flows (received directly from providers)
a. Ambulance
b. Demand for Service
c. Diagnostic Service
d. Emergency Care
e. Experience, Quality and Outcomes
f. Mental Health
g. Other Not Elsewhere Classified
h. Population Data
i. Public Health Screening
3) Mental Health Minimum Data Set (MHMDS)
4) Mental Health Learning Disability Data Set (MHLDDS)
5) Mental Health Services Data Set (MHSDS)
6) Maternity Services Data Set (MSDS)
7) Improving Access to Psychological Therapy (IAPT)
8) Child and Young People Health Service (CYPHS)
9) Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO using the Medeanalytics pseudonymisation tool and is then disseminated as follows:

1) Pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North East London Commissioning Support Unit for landing only.
2) North East London Commissioning Support Unit then pass the processed, Pseudonymised data provided under DSCRO contracts to the CCGs data processor, Medeanalytics International Limited where it is received, stored and processed
3) Records contain no national identifiers, but do contain the following local identifiers: [Local Patient Identifier], [Hospital Provider Spell No], [Unique CDS Identifier], [Attendance Identifier], and [A&E Attendance Number]
4) On arrival at Medeanalytics International Limited, one of the Medeanalytics International Limited operational staff then transfers the data from the secure landing zone to the ETL process. The Extract Transform Load (ETL) process then loads the data into the Medeanalytics International Limited system, where it is linked.
5) Allowed linkage is between the data sets contained within point 1 and the following data that is pseudonymised at source using the Medeanalytics pseudonymisation tool:
o Social Care data
o GP Practice data
o Community data
o Mental Health data
6) Access is fully controlled by Role Based Access Control (RBAC),, signed off by Caldicott Guardians/SIROs.
7) CCGs use the workflow features provided by the Medeanalytics International Limited Contract Validation Module to check recorded activity against contracts, and facilitate contract discussions with providers
8) CCG users use online features of the Medeanalytics International Limited system to produce reports, charts and dashboards to analyse the data for the purposes listed.
9) Pseudonymised patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis with access fully controlled by RBAC, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared.

Segregation
Data is held within the MedeAnalytics system, and is segregated according to contract.
Only MedeAnalytics operational staff (currently 4 individuals operating under full time MedeAnalytics employment contracts) have access to data prior to loading into the main system.
All staff at MedeAnalytics undertake compulsory IG Toolkit training every year.
All MedeAnalytics staff understand their responsibilities with regard to receiving, storage, processing and handling of data, and contractual sanctions that can result in disciplinary actions including dismissal for contraventions are included in employee contracts.

Specific processes are in place to setup new system users, all of which require Caldicott Guardian or SIRO sign-off in order to obtain user identities and passwords. Identities and passwords are restricted to specific subsets of data according to their Roles, so that a CCG user can only see data for their own CCG, and a GP user can only see data for their own GP Practice.

All access to data is managed under Roles-Based Access Controls

Access to data is provided through the MedeAnalytics front end interfaces, for on-line access; while it is reasonable and allowable for users to export the results displayed in reports, charts and dashboards, so that the results can be used in board presentations, reports and other management documents, bulk export of underlying linked data sets is not possible.

All accesses are audited

CCG staff are only able to access data pertinent to their own CCG

GP Practice staff are only able to access data for patients registered to their own practice

Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management service (operated by BMS) that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.

Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data

Only GP Practice users are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify have access to encrypted data, and can only access data to which they have rights under RBAC (which is CG/SIRO approved– within the CCG)

All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.

Commissioning – Pseudonymised – Local Flows
Management of services for non-contracted activities
The South Central and West Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1) Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Diagnostic Service
e. Primary Care Services
f. 3rd Party commissioning
Data quality management and pseudonymisation is completed within the DSCRO is then disseminated as follows:

1) Pseudonymised Local Provider data only is securely transferred from the DSCRO to South Central and West Commissioning Support Unit.
2) CCG staff then download the processed, Pseudonymised data from the South Central and West Commissioning Support Unit transfer service, and will then delete the data from the transfer service. The CCG analyse the data to see patient journeys for pathways or service design, re-design and commissioning.
3. Aggregation of required data for CCG management use will be completed by the CCG.
4. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreements
5. CCG staff then log in to the South Central and West Commissioning Support Unit transfer service and download the data to the CCG’s systems. South Central and West Commissioning Support Unit staff then delete the data from the transfer service.

GDPPR COVID-19 CCG - Pseudo — DARS-NIC-392341-F3R0B

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - Statutory exemption to flow confidential data without consent, Anonymised - ICO Code Compliant (Statutory exemption to flow confidential data without consent)

Legal basis: CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002, CV19: Regulation 3 (4) of the Health Service (Control of Patient Information) Regulations 2002; Health and Social Care Act 2012 - s261(5)(d)

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)

Sensitive: Sensitive

When:DSA runs 2020-08-17 — 2021-03-31 2021.01 — 2021.02.

Access method: One-Off, Frequent Adhoc Flow

Data-controller type: NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES CCG, NHS BEDFORDSHIRE, LUTON AND MILTON KEYNES ICB - M1J4Y

Sublicensing allowed: No

Datasets:

GPES Data for Pandemic Planning and Research (COVID-19)
COVID-19 General Practice Extraction Service (GPES) Data for Pandemic Planning and Research (GDPPR)

Objectives:

NHS Digital has been provided with the necessary powers to support the Secretary of State’s response to COVID-19 under the COVID-19 Public Health Directions 2020 (COVID-19 Directions) and support various COVID-19 purposes, the data shared under this agreement can be used for these specified purposes except where they would require the reidentification of individuals.

GPES data for pandemic planning and research (GDPPR COVID 19)
To support the response to the outbreak, NHS Digital has been legally directed to collect and analyse healthcare information about patients from their GP record for the duration of the COVID-19 emergency period under the COVID-19 Directions.
The data which NHS Digital has collected and is providing under this agreement includes coded health data, which is held in a patient’s GP record, such as details of:
• diagnoses and findings
• medications and other prescribed items
• investigations, tests and results
• treatments and outcomes
• vaccinations and immunisations

Details of any sensitive SNOMED codes included in the GDPPR data set can be found in the Reference Data and GDPPR COVID 19 user guides hosted on the NHS Digital website. SNOMED codes are included in GDPPR data.
There are no free text record entries in the data.

The Controller will use the pseudonymised GDPPR COVID 19 data to provide intelligence to support their local response to the COVID-19 emergency. The data is analysed so that health care provision can be planned to support the needs of the population within the CCG area for the COVID-19 purposes.

Such uses of the data include but are not limited to:

• Analysis of missed appointments - Analysis of local missed/delayed referrals due to the COVID-19 crisis to estimate the potential impact and to estimate when ‘normal’ health and care services may resume, linked to Paragraph 2.2.3 of the COVID-19 Directions.

• Patient risk stratification and predictive modelling - to highlight patients at risk of requiring hospital admission due to COVID-19, computed using algorithms executed against linked de-identified data, and identification of future service delivery models linked to Paragraph 2.2.2 of the COVID-19 Directions. As with all risk stratification, this would lead to the identification of the characteristics of a cohort that could subsequently, and separately, be used to identify individuals for intervention. However the identification of individuals will not be done as part of this data sharing agreement, and the data shared under this agreement will not be reidentified.

• Resource Allocation - In order to assess system wide impact of COVID-19, the GDPPR COVID 19 data will allow reallocation of resources to the worst hit localities using their expertise in scenario planning, clinical impact and assessment of workforce needs, linked to Paragraph 2.2.4 of the COVID-19 Directions:

The data may only be linked by the Data Controller or their respective Data Processor, to other pseudonymised datasets which it holds under a current data sharing agreement only where such data is provided for the purposes of general commissioning by NHS Digital. The Health Service Control of Patient Information Regulations (COPI) will also apply to any data linked to the GDPPR data.
The linked data may only be used for purposes stipulated within this agreement and may only be held and used whilst both data sharing agreements are live and in date. Using the linked data for any other purposes, including non-COVID-19 purposes would be considered a breach of this agreement. Reidentification of individuals is not permitted under this DSA.

LEGAL BASIS FOR PROCESSING DATA:
Legal Basis for NHS Digital to Disseminate the Data:
NHS Digital is able to disseminate data with the Recipients for the agreed purposes under a notice issued to NHS Digital by the Secretary of State for Health and Social Care under Regulation 3(4) of the Health Service Control of Patient Information Regulations (COPI) dated 17 March 2020 (the NHSD COPI Notice).
The Recipients are health organisations covered by Regulation 3(3) of COPI and the agreed purposes (paragraphs 2.2.2-2.2.4 of the COVID-19 Directions, as stated below in section 5a) for which the disseminated data is being shared are covered by Regulation 3(1) of COPI.

Under the Health and Social Care Act, NHS Digital is relying on section 261(5)(d) – necessary or expedient to share the disseminated data with the Recipients for the agreed purposes.

Legal Basis for Processing:
The Recipients are able to receive and process the disseminated data under a notice issued to the Recipients by the Secretary of State for Health and Social Care under Regulation 3(4) of COPI dated 20th March (the Recipient COPI Notice section 2).

The Secretary of State has issued notices under the Health Service Control of Patient Information Regulations 2002 requiring the following organisations to process information:

Health organisations

“Health Organisations” defined below under Regulation 3(3) of COPI includes CCGs for the reasons explained below. These are clinically led statutory NHS bodies responsible for the planning and commissioning of health care services for their local area

The Secretary of State for Health and Social Care has issued NHS Digital with a Notice under Regulation 3(4) of the National Health Service (Control of Patient Information Regulations) 2002 (COPI) to require NHS Digital to share confidential patient information with organisations permitted to process confidential information under Regulation 3(3) of COPI. These include:

• persons employed or engaged for the purposes of the health service

Under Section 26 of the Health and Social Care Act 2012, CCG’s have a duty to provide and manage health services for the population.

Regulation 7 of COPI includes certain limitations. The request has considered these limitations, considering data minimisation, access controls and technical and organisational measures.

Under GDPR, the Recipients can rely on Article 6(1)(c) – Legal Obligation to receive and process the Disclosed Data from NHS Digital for the Agreed Purposes under the Recipient COPI Notice. As this is health information and therefore special category personal data the Recipients can also rely on Article 9(2)(h) – preventative or occupational medicine and para 6 of Schedule 1 DPA – statutory purpose.

Expected Benefits:

• Manage demand and capacity
• Reallocation of resources
• Bring in additional workforce support
• Assists commissioners to make better decisions to support patients
• Identifying COVID-19 trends and risks to public health
• Enables CCGs to provide guidance and develop policies to respond to the outbreak
• Controlling and helping to prevent the spread of the virus

Outputs:

• Operational planning to predict likely demand on primary, community and acute service for vulnerable patients due to the impact of COVID-19
• Analysis of resource allocation
• Investigating and monitoring the effects of COVID-19
• Patient Stratification in relation to COVID-19, such as:
o Patients at highest risk of admission
o Frail and elderly
o Patients that are currently in hospital
o Patients with prescriptions related to COVID-19
o Patients recently Discharged from hospital
For avoidance of doubt these are pseudonymised patient cohorts, not identifiable.

Processing:

PROCESSING CONDITIONS:
Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.

Data Processors must only act upon specific instructions from the Data Controller.

All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract i.e.: employees, agents and contractors of the Data Recipient who may have access to that data).

The Recipients will take all required security measures to protect the disseminated data and they will not generate copies of their cuts of the disseminated data unless this is strictly necessary. Where this is necessary, the Recipients will keep a log of all copies of the disseminated data and who is controlling them and ensure these are updated and destroyed securely.

Onward sharing of patient level data is not permitted under this agreement. Only aggregated reports with small number suppression can be shared externally.

The data disseminated will only be used for COVID-19 GDPPR purposes as described in this DSA, any other purpose is excluded.

SEGREGATION:
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.

AUDIT
All access to data is auditable by NHS Digital in accordance with the Data Sharing Framework Contract and NHS Digital terms.
Under the Local Audit and Accountability Act 2014, section 35, Secretary of State has power to audit all data that has flowed, including under COPI.

DATA MINIMISATION:
Data Minimisation in relation to the data sets listed within the application are listed below:

• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner area).
and/or
• Patients treated by a provider where the CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy.
and/or
• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the CCG.

The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
- GDPPR COVID 19 Data
Pseudonymisation is completed within the DSCRO and is then disseminated as follows:
1. Pseudonymised GDPPR COVID 19 data is securely transferred from the DSCRO to the Data Controller / Processor
2. Aggregation of required data will be completed by the Controller (or the Processor as instructed by the Controller).
3. Patient level data may not be shared by the Controller (or any of its processors).

Project 5 — NIC-49738-Q2B0D

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y, N

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

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 - Other not elsewhere classified
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
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 - Ambulance, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Population Data, Public Health & Screening services, Not elsewhere classified
Local Provider Data - Acute, Ambulance, Community, Diagnostic Services, Emergency Care, Primary Care

Objectives:

Invoice Validation – Identifiable
As an approved Controlled Environment for Finance (CEfF), the CCG receives SUS data Identifiable at the level of NHS number according to S.251 CAG 7-07(a)(b)(c)/2013. The data is required for the purpose of invoice validation. The NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF.
Data within the CCG CEfF is used for Invoice Validation purposes, in accordance with CAG 7-07(a)(b)(c)/2013. As an approved Controlled Environment for Finance (CEfF), the CCG receives Identifiable SUS data for the purpose of invoice validation. The data is used to confirm the accuracy of backing data sets and will not be shared outside the CEfF.
Staff within the CEfF may refer to other resources and data in other computer systems (such as the MedeAnalytics service) while performing invoice validation, but no data flows between the systems, or outside the CEfF.
Commissioning – Pseudonymised - SUS
This flow is required for the activity known as Contract Validation which is part of General Commissioning. The description here represents a separate Pseudonymised flow that includes records for all patients (including Type 2 Objectors) so the CCG can manage challenges against 100% of their commissioning records. Local patient identifiers are needed to facilitate contractual discussions between providers and commissioners. Contract Validation is a separate model that runs in a completely isolated environment that has no connection to other data sources.
Commissioning – Identifiable – SUS, Local Provider Flows, Mental Health Datasets, Maternity, IAPT, CYPHS and DIDS
NHS numbers are required to leave NHS Digital in accordance with CAG 2-03(a)/2013, to be transferred to the CCG ASH secure landing zone operated by MedeAnalytics. Identifiable data arriving in the secure landing zone is then Pseudonymised, so that it can be loaded into the MedeAnalytics commissioning service to enable linking with Pseudonymised data from other sources (listed in this application) that have been Pseudonymised using the same process.
SUS and Local Flows
To use Pseudonymised data to provide intelligence to support commissioning of health services. The Pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple Pseudonymised datasets.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
These Pseudonymise data sets are used to provide accurate multi-provider pathway analysis.
Mental Health, Maternity, IAPT, CYPHS and DIDS
To use Pseudonymised data for the following datasets to provide intelligence to support commissioning of health services:
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
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 de-identified linked 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 NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.
Where analysis of pseudonymised patient records show that the associated patients could benefit from clinical interventions, GP Practice users who have legitimate relationships with the patients will be able to re-identify the patient records so that they can provide the interventions (direct care).

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
Commissioning
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
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.
All of the above lead to improved patient experience through more effective commissioning of services.
The introduction of integrated hubs is still underway, but the selection of pilot sites was informed by these analyses, MedeAnalytics will be used to evaluate the ongoing benefits of the hubs. Users fed back that:
Showing the number of benchmarked A&E admissions (and A&E attendances in the next analysis) from specific west Herts geographical locations in a heat map, will enable us and our providers to direct our finite health and social care (public health) resources more efficiently and effectively.
Users can better understand variation in their system, and make comparisons between populations and organisations in a fair and meaningful way with a greater understanding of what normal is. This will support routine opportunity analyses that they carry out in order to best target resources and best understand which activities have had a genuine benefit, and helped reduce costs to the system.
In addition, the platform provides access to comprehensive supporting information that commissioning organisations such as Clinical Commissioning Groups use to ensure that the services they commission are: * deliver the best outcomes for their patients * designed to cater for and meet the needs of the population they are responsible for;
* monitor condition prevalence within the population * identify health inequalities and work with local organisations and agencies to remove them
Also for Acute Trusts and other care providers it provides access to comprehensive supporting information that helps to: * ensure that the services they provide are of high quality, efficient and effective; * plan and re-engineer services to meet the changing requirements and developments in technology;
Direct measurement of the benefits associated with an enabling self-service system such as this is challenging, however, proxies can be provided through use metrics (number of individual users and frequency of use) as well as examples of decisions made by customers in the management and delivery of their services that have been supported by reports / information from the Mede tool

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events
Commissioning
General reporting
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.
Analytics Insights
Reports, charts and dashboards providing insights into:
1. 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
2. Data Quality and Validation measures allowing data quality checks on the submitted data
3. Contract Management and Modelling
4. 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
5. Understanding impacts and interdependency of care services

Processing:

South Central and West DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
Invoice Validation – Identifiable - SUS
1. Identifiable SUS Data is obtained from the SUS Repository by South Central West (SCW) Data Services for Commissioners Regional Office (DSCRO).
2. SCW DSCRO then pushes a one-way data flow of data Identifiable at the level of NHS number according to S.251 CAG 7-07(a)(b)(c)/2013 SUS data into SCW CSU Transfer Service.
3. The CSU lands the data only.
4. CCG CEfF staff log in to the SCW CSU Transfer service and download the Invoice Validation data to their CEfF. Once downloaded, CCG staff delete the data from the Transfer Service.
5. The CEfF conduct the following processing activities for invoice validation purposes:
a. Checking the individual is registered to the Clinical Commissioning Group (CCG) by using the derived commissioner field in SUS and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Backing information is received from providers directly into the CCG CEfF. Once received, it is checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. Are in relation to a patient registered with the CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
6. The CCG are notified by the CEfF that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved

Segregation
Data for this purpose is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CCG CEfF staff are able to access data in the CEfF from the transfer service, and only CCG CEfF staff operate the invoice validation process within the CCG’s CEfF. Data flows directly in to the CEfF from NHS Digital (via the CSU) and from the providers – it does not flow through other processors.
Commissioning – Pseudonymised – SUS
Contract Validation
1. North & East London (NEL) Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS data Identifiable by NHS number for the CCG from the SUS Repository.
2. NEL DSCRO then remove national identifiers to Pseudonymise the data
3. NEL DSCRO then pushes a one-way data flow of Pseudonymised data into North East London CSU Transfer Service.
4. The CSU lands the data only.
5. NEL CSU then pass the processed, Pseudonymised data provided under DSCRO contracts to the CCGs data processor, MedeAnalytics where it is received, stored and processed
6. Records contain no national identifiers, but do contain the following local identifiers: [Local Patient Identifier], [Hospital Provider Spell No], [Unique CDS Identifier], [Attendance Identifier], and [A&E Attendance Number]
7. On arrival at MedeAnalytics, one of the MedeAnalytics operational staff (currently 4 individuals) then transfers the data from the secure landing zone to the ETL process. The ETL process then loads the data into the MedeAnalytics Contract Validation Module’s database.
8. Access is fully controlled by RBAC, signed off by Caldicott Guardians/SIROs.
9. CCGs use the workflow features provided by the MedeAnalytics Contract Validation Module to check recorded activity against contracts, and facilitate contract discussions with providers
10. 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
Segregation
This data is processed separately by the DSCRO, and sent as a separate feed into the CSU Transfer Service. CSU staff use dedicated credentials to upload Pseudonymised data to a separate dedicated area within the MedeAnalytics secure landing zone.
The MedeAnalytics Contract Validation module is built using different technology than the rest of the service – it runs inside Mongo DB, on a different virtual server than the rest of the service, and does not connect to any other data sources.
Users login to the Contract Validation service using different usernames and passwords. The same username and password cannot be used for other MedeAnalytics services, which run on different technology.
Commissioning – Pseudonymised – Local Flows
Management of services for non-contracted activities
1. South Central West (SCW) Data Services for Commissioners Regional Office (DSCRO) obtains Identifiable local provider data for the CCG directly from Providers.
2. SCW DSCRO then remove national identifiers To Pseudonymise the data
3. CCG staff then download the processed, Pseudonymised data from the SCW CSU transfer service, and will then delete the data from the transfer service. The CCG analyse the data to see patient journeys for pathways or service design, re-design and commissioning.
4. Aggregation of required data for CCG management use will be completed 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 Agreements
6. CCG staff then log in to the CSU transfer service and download the data to the CCG’s systems outside the CEfF. CSU staff then delete the data from the transfer service.

Commissioning – Identifiable – SUS, Local Flows, Mental Health, MSDS, IAPT, CYPHS and DIDS General Commissioning
North East London DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
1. North & East London (NEL) DSCRO – part of NHS Digital –
a. Obtain Identifiable SUS data from the SUS Repository at NHS Digital.
b. Obtain Identifiable local provider data directly from Providers (as per Data Services for Commissioners Directions 2015).
c. Obtain Identifiable MHMDS, MHLDDS, MHMDS, MSDS, IAPT, CYPHS and DIDS data from Exeter.
2. Data quality management and standardisation of the data is completed by the DSCRO.
3. NEL DSCRO then remove records for all patients who have registered type 2 objections
4. Records contain one national identifier [NHS number], and the following local identifiers: [Local Patient Identifier], [Unique CDS Identifier], [Hospital Provider Spell No], [Attendance Identifier], [A&E Attendance Number]. These local identifiers are required to manage duplicates and monitor QIPP schemes.
5. The DSCRO then securely transfers the following to the CSU:
a. The SUS data Identifiable at the level of NHS number
b. The Local Provider data Identifiable at the level of NHS number
c. The MHMDS, MHLDDS, MHMDS, MSDS, IAPT, CYPHS and DIDS data Identifiable at the level of NHS number
6. The CSU lands the data only.
7. Data is then transferred to the MedeAnalytics secure landing zone where it is Pseudonymised using the MedeAnalytics Pseudonymisation at Source tool.
8. Pseudonymised data is then transferred from the MedeAnalytics secure landing zone to the MedeAnalytics General Commissioning service, where it is joined with historical data and other health and care data sets provided in direct support of NHS contracts, that have been Pseudonymised using the same process, and with the same keys.
9. Access is fully controlled by RBAC, signed off by Caldicott Guardians/SIROs.
10. CCG users login to the MedeAnalytics Software-as-a-Service environment, and use online reports, charts and dashboards to analyse the data for the purposes listed.
11. 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
Segregation
Data is held within the MedeAnalytics system, and is segregated according to contract.
Only MedeAnalytics operational staff (currently 4 individuals operating under full time MedeAnalytics employment contracts) have access to data prior to loading into the main system.
All staff at MedeAnalytics undertake compulsory IG Toolkit training every year.
All MedeAnalytics staff understand their responsibilities with regard to receiving, storage, processing and handling of data, and contractual sanctions that can result in disciplinary actions including dismissal for contraventions are included in employee contracts.
Specific processes are in place to setup new system users, all of which require Caldicott Guardian or SIRO sign-off in order to obtain user identities and passwords. Identities and passwords are restricted to specific subsets of data according to their Roles, so that a CCG user can only see data for their own CCG, and a GP user can only see data for their own GP Practice.
All access to data is managed under Roles-Based Access Controls
Access to data is provided through the MedeAnalytics front end interfaces, for on-line access; while it is reasonable and allowable for users to export the results displayed in reports, charts and dashboards, so that the results can be used in board presentations, reports and other management documents, bulk export of underlying linked data sets is not possible.
All accesses are audited
CCG staff are only able to access data pertinent to their own CCG
Only GP Practice are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify have access to encrypted data, and can only access data to which they have rights under RBAC (which is CG/SIRO approved – within the CCG). GP Practice staff are only able to access data for patients registered to their own practice.
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management service (operated by BMS) that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.

NHS Digital Data Release Register - reformatted

NHS Bedfordshire Ccg projects

DSfC - NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG - Comm — DARS-NIC-338789-M0T3Q

DSfC - NHS Bedfordshire CCG - RS — DARS-NIC-294268-B3Q6J

DSfC - NHS Bedfordshire CCG - IV & Comm — DARS-NIC-49738-Q2B0D

GDPPR COVID-19  CCG - Pseudo — DARS-NIC-392341-F3R0B

Project 5 — NIC-49738-Q2B0D

GDPPR COVID-19 CCG - Pseudo — DARS-NIC-392341-F3R0B