NHS Digital Data Release Register - reformatted

NHS West Yorkshire Icb - 03r projects

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


DSfC - NHS Wakefield CCG - Comm, IV, RS — DARS-NIC-527503-Z3W0N

Opt outs honoured: Anonymised - ICO Code Compliant, Identifiable (Mixture of confidential data flow(s) with support under section 251 NHS Act 2006 and non-confidential data flow(s))

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

Purposes: No (Sub ICB Location)

Sensitive: Sensitive

When:DSA runs 2021-08-01 — 2024-07-31

Access method: Frequent Adhoc Flow

Data-controller type: NHS WEST YORKSHIRE ICB - 03R

Sublicensing allowed: No

Datasets:

  1. Acute-Local Provider Flows
  2. Ambulance-Local Provider Flows
  3. Children and Young People Health
  4. Civil Registration - Births
  5. Civil Registration - Deaths
  6. Community Services Data Set
  7. Community-Local Provider Flows
  8. Demand for Service-Local Provider Flows
  9. Diagnostic Imaging Dataset
  10. Diagnostic Services-Local Provider Flows
  11. Emergency Care-Local Provider Flows
  12. e-Referral Service for Commissioning
  13. Experience, Quality and Outcomes-Local Provider Flows
  14. Improving Access to Psychological Therapies Data Set_v1.5
  15. Maternity Services Data Set
  16. Medicines dispensed in Primary Care (NHSBSA data)
  17. Mental Health and Learning Disabilities Data Set
  18. Mental Health Minimum Data Set
  19. Mental Health Services Data Set
  20. Mental Health-Local Provider Flows
  21. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
  22. National Diabetes Audit
  23. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  24. Patient Reported Outcome Measures
  25. Personal Demographic Service
  26. Population Data-Local Provider Flows
  27. Primary Care Services-Local Provider Flows
  28. Public Health and Screening Services-Local Provider Flows
  29. Summary Hospital-level Mortality Indicator
  30. SUS for Commissioners

Objectives:

INVOICE VALIDATION
Invoice validation is part of a process by which providers of care or services get paid for the work they do.

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

The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.

Invoice Validation with be conducted by North of England CSU and Liaison Financial Services Ltd.

Liaison Financial Services conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.

RISK STRATIFICATION
Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.

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

Risk Stratification will be conducted by NHS Wakefield CCG

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:

1. Secondary Uses Service (SUS+)
2. Local Provider Flows
- Acute
- Ambulance
- Community
- Demand for Service
- Diagnostic Service
- Emergency Care
- Experience, Quality and Outcomes
- Mental Health
- Other Not Elsewhere Classified
- Population Data
- Primary Care Services
- Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
12. Civil Registries Data (CRD) (Births)
13. Civil Registries Data (CRD) (Deaths)
14. National Diabetes Audit (NDA)
15. Patient Reported Outcome Measures (PROMs)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)

Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.

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

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

Processing for commissioning will be conducted by NHS North of England Commissioning Support Unit.

Yielded Benefits:

The data has been used to undertake CCG level analysis, identifying efficiencies in terms of reporting, analytical resource and more importantly, allowing benchmark analysis to be undertaken to identify variation and opportunities for sharing good practice. A recent example is analysis of A&E attendances – using the data to analyse why, who and how people are attending A&E and if there is commonality across all places. The data and supporting analysis is being used by the CCG and forms part of the wider health inequality work. Having access to a single dataset at system level allows analysts across the CCG to work collaboratively, share data, resource and expertise (ensuring one version of the truth) in a safe and structured way. Prior to Data Sharing Agreements with NHS Digital, each area would produce a report and share data/analysis via email. The DSA also supports the CCG’s future BI model and way of working. Routine use of the dataset allows the CCG to collect data from Trusts within the CCG’s area without increasing the burden of data collection, processing, and submissions. This become a key part of the CCG’s reporting system (LMS board reports and the reporting of stillbirths, breastfeeding initiation, smoking at birth, continuity of carer etc.). As the role of the CCG develops, this access and use of routine data sources is critical to not overwhelming the CCG’s partners in Trusts. Another key benefit of this data is the ability to break down existing performance and outcome indicators by other population characteristics. The data allows the CCG to evaluate how ethnic background and deprivation of residence impact the level of care and outcomes received. This heightens the CCG’s ability to identify and target health inequities in a way the maternity system has not been able to do before. Working at this level means that the CCG are able to do this once for all Trusts, aiding local efforts, but can also combine the results of the CCG to increase the power of the data.

Expected Benefits:

INVOICE VALIDATION
The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by:
1. Ensuring that activity is fully financially validated.
2. Ensuring that service providers are accurately paid for the patients treatment.
3. Enabling services to be planned, commissioned, managed, and subjected to financial control.
4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they are responsible.
5. Fulfilling commissioners duties to fiscal probity and scrutiny.
6. Ensuring full financial accountability for relevant organisations.
7. Ensuring robust commissioning and performance management.
8. Ensuring commissioning objectives do not compromise patient confidentiality.
9. Ensuring the avoidance of misappropriation of public funds.

INVOICE VALIDATION - Liaison Financial Services Ltd
Expected measurable benefits to health and/or social care including target date:
1. Financial validation of activity
2. CCG Budget control
3. Assurances over the robustness of internal control mechanisms relating to the payment of invoices and/or suggested improvements
4. Identification and recovery of monies which would otherwise be lost
5. Meeting commissioning objectives without compromising patient confidentiality
6. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care
7. Benefit delivered 3-9 months from receiving data, depending on number of claims to investigate and resolve

RISK STRATIFICATION
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
2. Improved quality of services through reduced emergency re-admissions, 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.

COMMISSIONING
1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways.
a. Analysis to support full business cases.
b. Develop business models.
c. Monitor In year projects.
2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3. Health economic modelling using:
a. Analysis on provider performance against 18 weeks wait targets.
b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC).
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. Financial and Non-financial validation of activity.
c. Successful delivery of integrated care within the CCG.
d. Checking frequent or multiple attendances to improve early intervention and avoid admissions.
e. Case management.
f. Care service planning.
g. Commissioning and performance management.
h. List size verification by GP practices.
i. Understanding the care of patients in nursing homes.
6. Feedback to NHS service providers on data quality at an aggregate and individual record level – only on data initially provided by the service providers.
7. Improved planning by better understanding patient flows through the healthcare system, thus allowing commissioners to design appropriate pathways to improve patient flow and allowing commissioners to identify priorities and identify plans to address these.
8. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services and early intervention of appropriate care.
9. Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
10. Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
11. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
12. Better understanding of contract requirements, contract execution, and required services for management of existing contracts, and to assist with identification and planning of future contracts
13. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.
14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.
15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.
16. Provision of indicators of health problems, and patterns of risk within the commissioning region.
17. Support of benchmarking for evaluating progress in future years.
18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people.
19. Assists commissioners to make better decisions to support patients and drive changes in health care
20. Allows comparisons of providers performance to assist improvement in services – increase the quality
21. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.
22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one).
23. Monitoring of entire population, as a pose to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
27. Understand admissions linked to overprescribing.
28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.

Outputs:

INVOICE VALIDATION
1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.
2. Outputs from the CEfF will enable accurate production of budget reports, which will:
a. Assist in addressing poor quality data issues
b. Assist in business intelligence
3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.
4. Budget control of the CCG.

INVOICE VALIDATION - Liaison Financial Services Ltd
1. Validation of Continuing Healthcare related invoices and payments
2. Independent Identification of potential overpayments made by the CCG through invoice validation
3. Liaising with providers with a view to recouping these monies
4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.
5. Reviews take 3-9 months depending on number of claims to investigate and resolve
6. Liaison Financial Services would repeat the exercise 2-3 years later
7. CCGs could request reviews to be done more frequently
8. SUS+ would only be requested each time a review was completed, and could be requested
at different times as independent reviews

RISK STRATIFICATION
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.

CCGs will be able to:
3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.
4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.
5. Identify patients at risk of deterioration and providing effective care.
6. Reduce in the difference in the quality of care between those with the best and worst outcomes.
7. Re-design care to reduce admissions.
8. Set up capitated budgets – budgets based on care provided to the specific population.
9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.
11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.
12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.
13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.
14. Analyse based on specific diseases

In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.

COMMISSIONING
1. Commissioner reporting:
a. Summary by provider view - plan & actuals year to date (YTD).
b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
c. Summary by provider view - activity & finance variance by POD.
d. Planned care by provider view - activity & finance plan & actuals YTD.
e. Planned care by POD view - activity plan & actuals YTD.
f. Provider reporting.
g. Statutory returns.
h. Statutory returns - monthly activity return.
i. Statutory returns - quarterly activity return.
j. Delayed discharges.
k. Quality & performance referral to treatment reporting.
2. Readmissions analysis.
3. Production of aggregate reports for CCG Business Intelligence.
4. Production of project / programme level dashboards.
5. Monitoring of acute / community / mental health quality matrix.
6. Clinical coding reviews / audits.
7. Budget reporting down to individual GP Practice level.
8. GP Practice level dashboard reports.
9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports
10. Data Quality and Validation measures allowing data quality checks on the submitted data
11. Contract Management and Modelling
12. Patient Stratification, such as:
o Patients at highest risk of admission
o High cost activity uses (top 15%)
o Frail and elderly
o Patients that are currently in hospital
o Patients with most referrals to secondary care
o Patients with most emergency activity
o Patients with most expensive prescriptions
o Patients recently moving from one care setting to another
i. Discharged from hospital
ii. Discharged from community
13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.
14. Validation of programs implemented to improve patient pathway
15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.
16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.
17. Removal of patients from Risk Stratification reports.
18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.
19. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand.
20. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters.
21. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals.
22. Allow Commissioners to better protect or improve the public health of the total local patient population
23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population
24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline.
25. Investigate mortality outcomes for trusts
26. Identify medication prescribing trends and their effectiveness.
27. Linking prescribing habits to entry points into the health and social care system
28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy)


DSfC - NHS Wakefield CCG; RS, IV & Comm. — DARS-NIC-90713-T3K1V

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

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 – s261(2)(b)(ii)

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

Sensitive: Sensitive

When:DSA runs 2019-09-20 — 2022-09-19 2018.06 — 2021.05.

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

Data-controller type: NHS WAKEFIELD CCG, NHS WEST YORKSHIRE ICB - 03R

Sublicensing allowed: No

Datasets:

  1. Acute-Local Provider Flows
  2. Ambulance-Local Provider Flows
  3. Children and Young People Health
  4. Community-Local Provider Flows
  5. Demand for Service-Local Provider Flows
  6. Diagnostic Imaging Dataset
  7. Diagnostic Services-Local Provider Flows
  8. Emergency Care-Local Provider Flows
  9. Experience, Quality and Outcomes-Local Provider Flows
  10. Improving Access to Psychological Therapies Data Set
  11. Maternity Services Data Set
  12. Mental Health and Learning Disabilities Data Set
  13. Mental Health Minimum Data Set
  14. Mental Health Services Data Set
  15. Mental Health-Local Provider Flows
  16. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  17. Population Data-Local Provider Flows
  18. Primary Care Services-Local Provider Flows
  19. Public Health and Screening Services-Local Provider Flows
  20. SUS for Commissioners
  21. Community Services Data Set
  22. National Cancer Waiting Times Monitoring DataSet (CWT)
  23. Civil Registration - Births
  24. Civil Registration - Deaths
  25. National Diabetes Audit
  26. Patient Reported Outcome Measures
  27. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
  28. Improving Access to Psychological Therapies Data Set_v1.5

Objectives:

Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so they are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets and will not be used further.
The legal basis for this to occur is under Section 251 of NHS Act 2006.
Invoice Validation with be conducted by North of England Commissioning Support Unit.
The CCG are advised by North of England Commissioning Support Unit whether payment for invoices can be made or not.

Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides a forecast of future demand by identifying high risk 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.
The legal basis for this to occur is under Section 251 of NHS Act 2006 (CAG 7-04(a)).
Risk Stratification will be conducted by eMBED Health Consortium.

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)
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 eMBED Health Consortium.

Yielded Benefits:

Expected Benefits:

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

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

All of the above lead to improved patient experience through more effective commissioning of services.

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

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 (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.

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.

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.

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 of interest of the applicant.

The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.

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).

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.

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

Invoice Validation
1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the North of England Commissioning Support Unit.
3. The CSU 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 North of England Commissioning Support Unit CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

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 eMBED Health Consortium, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to eMBED Health Consortium.
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 eMBED Health Consortium 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)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor – eMBED Health Consortium via North of England 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), and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to North of England Commissioning Support Unit.
2. North of England Commissioning Support Unit add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning
b. Check recorded activity against contracts or invoices and facilitate discussions with providers
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. North of England Commissioning Support Unit then pass the processed, pseudonymised and linked data to both eMBED Health Consortium and the CCG. eMBED Health Consortium analyse the data 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
5. Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit, eMBED Health Consortium or the CCG as instructed by the CCG.
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.


GDPPR COVID-19 – CCG - Pseudo — DARS-NIC-384781-J8H2K

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 2020-08-06 — 2021-03-31 2021.01 — 2021.05.

Access method: One-Off, Frequent Adhoc Flow

Data-controller type: NHS WAKEFIELD CCG, NHS WEST YORKSHIRE ICB - 03R

Sublicensing allowed: Yes, No

Datasets:

  1. GPES Data for Pandemic Planning and Research (COVID-19)
  2. COVID-19 Ethnic Category Data Set
  3. COVID-19 Vaccination Status

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, including those set out below, through:
• establishing and operating information systems to collect and analyse data in connection with COVID-19 for COVID-19 purposes, and
• developing and operating information and communication systems to deliver services in connection with COVID-19 for COVID-19 purposes,
Such COVID-19 purposes include the following:
a) Paragraph 2.2.2 of the COVID-19 Directions: identifying and understanding information about patients or potential patients with or at risk of COVID-19 , information about incidents of patient exposure to COVID-19 and the management of patients with or at risk of COVID-19 including: locating, contacting, screening, flagging and monitoring such patients and collecting information about and providing services in relation to testing, diagnosis, self-isolation, fitness to work, treatment, medical and social interventions and recovery from COVID-19
b) Paragraph 2.2.3 of the COVID-19 Directions: understanding information about patient access to health services and adult social care services as a direct or indirect result of COVID-19 and the availability and capacity of those services
c) Paragraph 2.2.4 of the COVID-19 Directions: monitoring and managing the response to COVID-19 by health and social care bodies and the Government including providing information to the public about COVID-19 and its effectiveness and information about capacity, medicines, equipment, supplies, services and the workforce within the health services and adult social care services

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 above 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 patients 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 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 set out above.

Such uses cases 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 to come and estimate of 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 reidentification of a cohort of patients specifically at risk.

• 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 be only be linked by the Recipient to other datasets which it holds under a current data sharing agreement (where such data is provided for the purposes of commissioning) with NHS Digital. Reidentification of individuals is not permitted under this DSA. 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.

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.

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 CCG’s 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 COVID-19
• Analysis of resource allocation due to the impact of COVID-19
• 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

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 keep their cut of the electronic disseminated data in an encrypted form and 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 is not permitted under this agreement.

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).
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).


Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — DARS-NIC-204520-B1V2G

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), Network, Sub ICB Location)

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

When:DSA runs 2019-03-01 — 2020-01-31 2019.05 — 2021.05.

Access method: System Access
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)

Data-controller type: NHS WAKEFIELD CCG, NHS WEST YORKSHIRE ICB - 03R

Sublicensing allowed: No

Datasets:

  1. National Cancer Waiting Times Monitoring DataSet (CWT)
  2. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)

Objectives:

Improvements for Cancer patients

The independent Cancer Taskforce set out an ambitious vision for improving services, care and outcomes for everyone with Cancer: fewer people getting Cancer, more people surviving Cancer, more people having a good experience of their treatment and care, whoever they are and wherever they live, and more people being supported to live as well as possible after treatment has finished.


Cancer Alliances

Cancer Alliances, which have been set up across England, are key to driving the change needed across the country to achieve the Taskforce’s vision. Bringing together local clinical and managerial leaders from providers and commissioners who represent the whole Cancer pathway, Cancer Alliances provide the opportunity for a different way of working to improve and transform Cancer services. Cancer Alliance partners will take a whole population, whole pathway approach to improving outcomes across their geographical ‘footprints’, building on their relevant Sustainability and Transformation Plans (STPs). They will bring together influential local decision-makers and be responsible for directing funding to transform services and care across whole pathways, reducing variation in the availability of good care and treatment for all people with Cancer, and delivering continuous improvement and reduction in inequality of experience. They will particularly focus on leading transformations at scale to improve survival, early diagnosis, patient experience and long-term quality of life. Successful delivery will be shown in improvements in ratings in the Clinical Commissioning Group (CCG) Improvement and Assessment Framework (IAF), including, importantly, in the 62 day wait from referral to first treatment standard.
https://www.england.nhs.uk/publication/ccg-iaf-methodology-manual/


Cancer Wait Times (CWT) system

The Cancer Wait Times (CWT) system collects and validates the National Cancer Waiting Times Monitoring Data Set (NCWTMDS), allowing performance to be measured against operational Cancer standards. Data is validated and records merged to the same pathway to cover the period from referral to first definitive treatment for Cancer and any additional subsequent treatments.

The CWT system then determines whether the operational standard(s) that apply were met or not for the patient and the accountable provider(s). The CWT system holds NCWTMDS in a series of pre-aggregated static reports. These reports are available monthly and quarterly data (aligned with the National Statistics for Cancer Waiting Times published by NHS England). Users can query the CWT system to generate reports to feedback on the progress towards meeting these targets.

West Yorkshire and Harrogate Cancer Alliance

Wakefield CCG will directly access the Cancer Waiting Times System on behalf of West Yorkshire and Harrogate Cancer Alliance across West Yorkshire and Harrogate. West Yorkshire and Harrogate Cancer Alliance is hosted by Wakefield CCG and covers a population of 2.7 million people.

Wakefield CCG works with health organisations across West Yorkshire and Harrogate including 6 acute providers, 9 clinical commissioning groups, 3 community providers and 9 hospices.

Acute Providers

Airedale NHS Foundation Trust
Bradford Teaching Hospitals NHS Foundation Trust
Calderdale and Huddersfield NHS Foundation Trust
Harrogate and District NHS Foundation Trust
Leeds Teaching Hospitals NHS Trust
Mid Yorkshire Hospitals NHS Trust

CCGs

NHS Airedale, Wharfdale and Craven CCG
NHS Bradford City CCG
NHS Bradford Districts CCG
NHS Calderdale CCG
NHS Greater Huddersfield CCG
NHS Harrogate and Rural District CCG
NHS Leeds CCG
NHS North Kirklees CCG
NHS Wakefield CCG

Community Providers

Bradford District Care Trust
Leeds Community Healthcare NHS Trust
Locala

Hospices

Manorlands, Bradford
Marie Curie Hospice, Bradford
Overgate Hospice, Calderdale
St Micheals, Harrogate
Kirkwood Hospice, Huddersfield
St Gemma's, Leeds
Wheatfield House, Leeds
Wakefield Hospice
The Prince of Wales Hospice, Pontefract

Data access

The CWT system provides one organisation (the lead organisation) representing each Cancer Alliance, with access to the following;
a) Aggregate reports (which may include unsuppressed small numbers)
b) Pseudonymised record level data - users can directly download this data from the CWT system
c) I-View Plus tool

Lead organisations will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' CCG of responsibility. This Cancer Alliance is limited to West Yorkshire and Harrogate Cancer Patients.

A) Aggregate reports including small numbers
Aggregate data is available in the form of reports at Provider (Trust) and Clinical Commissioning Group (CCG) level.
Small numbers may be included in the aggregate data reports and are essential for analyses carried out by lead organisations.

Investigating breaches
Lead organisations routinely monitor performance and standards using the CWT system, particularly in relation to breaches of the 62 day wait target. Due to the large number of potential Trust/CCG combinations, breach counts could result in small numbers as in some cases there are less than 6 breaches in a whole year. Given that financial penalties are linked to target breaches counts must accurately reflect the true percentage without suppression.

Mitigating risk of re-identification
Risk of disclosure is minimised as the dataset does not include patient demographics (increasing risk of re-identification) that may allow users to identify an individual e.g. there are no age, ethnic categories or geographic breakdowns.

Additionally, the aggregation categories are such that the data is not at a lesser granular level e.g. the source NCWTMDS data collects information at ICD diagnosis code level, but the CWT system aggregates at tumour group level – e.g. Head & Neck, Upper GI, lower GI, Breast etc.

B) Pseudonymised record level extracts
Lead organisations will access record level pseudonymised data which includes the system generated pseudo CWT patient ID.

Any record level data extracted from the system will not be processed outside of the authorised users of the system.

C) i-View Plus .
iView Plus uses cube functionality to allow lead organisations to produce graphs, charts and tabulations from the data through the construction of queries. The data in iView plus is split by operational standard being measured and can then be analysed against a range of dimensions collected in the data and measures such as count, percentage and median. The outputs of iView Plus are aggregate, and no record level data can be obtained, however some queries may result in small numbers and these currently have limited disclosure control applied, see A) for further explanation.
iView Plus holds published data, the lowest organisational granularity is trust level, data can also be aggregated to CCG level and other health hierarchies.

Lead organisations will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.

Lead organisations use of the data will fall into two separate categories, each requiring different levels of suppression, and onward sharing both within the Cancer Alliance and with wider NHS stakeholders;

Purpose One - Aggregate local reports
Generation of routine Cancer Waiting Times reports at Provider (Trust) or CCG level. Lead organisations will access a summary of the totals for the Providers (Trust) and CCGs that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCGs they are aligned to). This analysis would then be shared with the providers and commissioners and used to inform service improvement by providing benchmarked comparable data. The format of this report would be in a tabulated or graphical form (i.e. not record level) but may contain small numbers. An example of where small numbers would not be suppressed would be in relation to cases of breaches against a standard where small numbers would be essential to ensure the report is meaningful.

Examples of this type of analysis include:
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs across the geography
b. Analysis of Cancer Waiting Times performance by treatment modality
c. Grouping length of waits for standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Reviewing waits between surgery and radiotherapy for Head and Neck Cancer patients with a maximum recommended wait of 6 weeks
h. Reviewing routes to diagnosis of patients
i. Quantifying treatment volumes by provider organisation including analysis treatment rates

Purpose Two - Sharing of record level data (including free text breach reasons) with providers and commissioners responsible for direct patient care for that patient. This will be for local clinical audit purposes.

The two broad purposes for this would be;

1) To support local clinical audit work
2) Investigate individual outliers to the national standards

Pathway analysis will be undertaken, identifying trends in reasons for breaches. The analysis will inform system wide pathway improvements and compliance to the national standards. Examples of potential changes to achieve this could be to support trusts in additional resources and processes and also to facilitate discuss between trusts for example in reaching agreement for diagnostics between trusts.

Examples of the types of reasons for this include;
a. Patients waiting excessively long period of time to seen of received treatment
b. Free text breach reasons identifying areas of concern which require more detail or clarification from provider
c. Identification of 28 day standard exceptions - National guidance states patients who are diagnosed with cancer should be informed face to face, this would highlights numbers of patients who are not told in person by provider
d. Audits to review orphan records which require local providers to review local patients records

Record level data (pseudonymised) will be shared via NHS.net email accounts and access will be controlled by password protecting all files.




Yielded Benefits:

To date West Yorkshire and Harrogate Cancer Alliance has mainly received cancer waits data in the form of pre-analysed reports from NHS England. These have enabled the Alliance and its Board to identify priority pathways and parts of pathways for remedial action to deliver improved clinical pathways and faster diagnosis and treatment. To date there has been no specific use of data from the Open Exeter system.

Expected Benefits:

1) Benefits type: Supporting delivery of CWT standards
The Cancer Waiting Times standards are key operational standards for the NHS, which aim to reduce the waits for diagnosis and treatment for Cancer patients, which will support improvements to survival rates and improve patient experience. This includes the new 28 day faster diagnosis standard being introduced as a standard from April 2020.
A key enabler to achieve these standards, and thus improve survival and patient experience is the role of Cancer Alliances locally to work with providers and commissioners to improve patient pathways. Access to the Cancer Waiting Times data as detailed in the above will enable Cancer Alliances to have informed discussions and allocate resources optimally to improve performance against these standards. It will also enable Cancer Alliances to work with local providers and commissioners to identify outliers against the standards, and mitigate the risk of similar delays for other patients.

Improvement would be expected on an on-going basis with standards already in place for nine standards:-
• 2 week wait urgent GP referral – 93%
• 2 week wait breast symptomatic – 93%
• 31 day 1st treatment - 96%
• 31 day subsequent surgery – 94%
• 31 day subsequent drugs – 98%
• 31 day subsequent radiotherapy – 94%
• 62 day (GP) referral to 1st treatment – 85%
• 62 day (screening ) referral to 1st treatment – 90%
• 62 day upgrade to 1st treatment – locally agreed standard
In addition this access and use of data will be key in delivering the new 28 day faster diagnosis standard being introduced from 2020

2) Benefits type: Improvements beyond constitutional standards
This access and resulting analysis will enable Cancer Alliances to undertake local analysis beyond the Cancer Waiting times operational standards to support improvements to Cancer patients pathways beyond those already achieved by improving performance against standard set. This could include reviewing times between treatments, or treatment rates.

The overall aim of this type of additional analysis would be to support improvements to Cancer patients survival and experience. The Cancer Taskforce recommendation set out a number of ambitions to be met nationally and locally by 2020 including improving 1 year survival for Cancer to 75%, and improving the proportions of patients staged 1 or 2 to 62%. For both of these improvements to the diagnostic and treatment pathways are key, and require Cancer Alliances to be able to analyse the Cancer Waiting Times dataset to identify sub-optimum pathways and resulting improvements.

Outputs:

Outputs fall into the following categories:

1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs.
b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions
c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays.
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Outlier identification including exceptionally long waits to inform individual queries to providers

2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patient’s outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust.

The overarching aim of all future analysis/outputs is to inform priorities and potential investment to improve Cancer pathways including reducing Cancer incidence and mortality, improving Cancer survival, improving patient experience, improving service efficiency and meeting national constitution standards relating to Cancer patients.


Processing:

Access to the Cancer Wait Times (CWT) System will enable Cancer Alliances to undertake a wide range of locally-determined and locally-specific analyses to support the Cancer Taskforce vision for improving services, care and outcomes for everyone with Cancer.

As Wakefield CCG are acting as the lead organisation in a Cancer Alliance their access is via the same route as other Cancer Alliances i.e via the Cancer Wait Times (CWT) System. The team doing this processing within Wakefield CCG are separate from the the commissioning team and would not have access to data provide via the DSCRO route. Additionally any separate agreement that Wakefield CCG have to access CWT may include other processors and purposes.

Only the lead organisation Wakefield CCG will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the Wakefield CCG servers. Role Based Access Control prevents access to data downloads to employees outside of the analytical team responsible for producing outputs; the Health and Care Partnership Analytics Team and Wakefield CCG analytics team.

The CWT system is hosted by NHS Digital, access to and usage of the system is fully auditable. Users must comply with the use of the data as specified in this agreement. The CWT system complies with the requirements of NHS Digital Code of Practice on Confidential Information, the Caldicott Principles and other relevant statutory requirements and guidance to protect confidentiality.

Calderdale and Huddersfield NHS Foundation Trust, supply IT infrastructure and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Access to the CWT system will be granted to individual users only when a valid Data Usage Certificate (DUC) form is submitted to NHS Digital via the lead organisations Senior Information Risk Officer (SIRO), and where there is a valid Data Sharing Agreement between the lead organisation and NHS Digital.

Approved users will log into the system via an N3 connection and will use a Single Sign-On (users are prompted to create a unique username and password).

Wakefield CCG users will access:

a) Aggregate reports (which may include unsuppressed small numbers)

b) Pseudonymised record level data - users can directly download this data from the CWT system

c) I-View Plus tool (aggregated - access to produce graphs, charts/tabulations from the data through the construction of queries). This will give users access to run bespoke analysis on pre-defined measures and dimensions. It delivers the same data that is available through the reports and record level downloads (i.e. it will not contain patient identifiable data).

Any record level data extracted from the system will not be processed outside of Wakefield CCG unless otherwise specified in this agreement. Following completion of the analysis the record level data will be securely destroyed.

Users are not permitted to upload data into the system.

Data will only be available for the Providers (Trust) and CCGs that are treating cancer patients where they have a commissioning responsibility for that patient (based on the CCGs that this Cancer Alliance is aligned to).

The data will only be shared with other members of the Cancer Alliance in the format described in purpose 1 and purpose 2 of this agreement. The primary method for sharing outputs is nhs.net email.

Aggregate data/ graphical outputs may be shared via e-mail; for example as part of Alliance meeting papers.

Where record level data is shared with individual trusts these are shared only with trust(s) who were involved in the direct care of the patient, only via NHS.net email accounts.

Data will only be shared as described in purpose one and purpose two of this agreement and where recipient organisations hold a valid Data Sharing Agreement with NHS Digital to access Cancer Waiting Times data.

Training on the CWT system is not required as it is a data delivery system and it does not provide functionality to conduct bespoke detailed analysis. User guides are available for further assistance.

Access to the CWT system data is restricted to Cancer Alliance employees who are substantively employed by the Data Controller in fulfilment of their public health function.

The Cancer Alliances will use the data to produce a range of quantitative measures (counts, crude and standardised rates and
ratios) that will form the basis for a range of statistical analyses of the fields contained in the supplied data.
Typical uses will include:
1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and CCGs.
b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions
c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays.
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Outlier identification including exceptionally long waits to inform individual queries to providers

2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patient’s outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust.

The members of the Health and Care Partnership Analytics Team who will process the data are all substantive employees of Wakefield CCG.





DSfC - DARS West Yorkshire & Harrogate - Comm — DARS-NIC-333880-G4H3T

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 - 'Other dissemination of information', 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 2020-04-01 — 2023-03-31 2020.05 — 2021.03.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS BRADFORD DISTRICT AND CRAVEN CCG, NHS CALDERDALE CCG, NHS KIRKLEES CCG, NHS WAKEFIELD CCG, NHS BRADFORD DISTRICT AND CRAVEN CCG, NHS CALDERDALE CCG, NHS KIRKLEES CCG, NHS LEEDS CCG, NHS WAKEFIELD CCG, NHS WEST YORKSHIRE ICB - 02T, NHS WEST YORKSHIRE ICB - 03R, NHS WEST YORKSHIRE ICB - 36J, NHS WEST YORKSHIRE ICB - X2C4Y, NHS WEST YORKSHIRE ICB - 02T, NHS WEST YORKSHIRE ICB - 03R, NHS WEST YORKSHIRE ICB - 15F, NHS WEST YORKSHIRE ICB - 36J, NHS WEST YORKSHIRE ICB - X2C4Y

Sublicensing allowed: No

Datasets:

  1. Acute-Local Provider Flows
  2. Ambulance-Local Provider Flows
  3. Children and Young People Health
  4. Civil Registration - Births
  5. Civil Registration - Deaths
  6. Community Services Data Set
  7. Community-Local Provider Flows
  8. Demand for Service-Local Provider Flows
  9. Diagnostic Imaging Dataset
  10. Diagnostic Services-Local Provider Flows
  11. Emergency Care-Local Provider Flows
  12. Experience, Quality and Outcomes-Local Provider Flows
  13. Improving Access to Psychological Therapies Data Set
  14. Maternity Services Data Set
  15. Mental Health and Learning Disabilities Data Set
  16. Mental Health Minimum Data Set
  17. Mental Health Services Data Set
  18. Mental Health-Local Provider Flows
  19. National Cancer Waiting Times Monitoring DataSet (CWT)
  20. National Diabetes Audit
  21. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  22. Patient Reported Outcome Measures
  23. Population Data-Local Provider Flows
  24. Primary Care Services-Local Provider Flows
  25. Public Health and Screening Services-Local Provider Flows
  26. SUS for Commissioners
  27. e-Referral Service for Commissioning
  28. Personal Demographic Service
  29. Summary Hospital-level Mortality Indicator
  30. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
  31. Improving Access to Psychological Therapies Data Set_v1.5

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)
- Civil Registries Data (CRD) (Births)
- Civil Registries Data (CRD) (Deaths)
- National Diabetes Audit (NDA)
- Patient Reported Outcome Measures (PROMs)

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

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

Processing for commissioning will be conducted by North of England Commissioning Support Unit

Yielded Benefits:

The data sharing agreement covering CCGs in West Yorkshire has enabled the CCGs to benchmark performance at a West Yorkshire level which will lead to improvements across the area. This has initially been focussed on the MHSDS, Community and maternity data sets. The CCGs are also able to more readily share insight and expertise with colleagues in the other CCGs as they are all able to use common data sets.

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.
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:

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

Processing:

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

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

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

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

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

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
ONWARD SHARING:
Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.

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


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

Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.

All access to data is auditable by NHS Digital.

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

For the purpose of Commissioning:
• Patients who are normally registered and/or resident within the CCGs regions (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where the CCGs ares 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.

This includes data that was previously under a different organisation name but has now merged into this CCG


Calderdale & Huddersfield NHS Foundation Trust supply provide IT Infrastructure and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Pulsant and IT Professional Services 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.

N3i Limited supply IT infrastructure for North of England Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement.

A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting

Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation).

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

Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:

Data Processor 1 – North of England Commissioning Support Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs) only is securely transferred from the DSCRO to North of England Commissioning Support Unit.
2. North of England Commissioning Support Unit add derived fields by using existing data, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. North of England 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 of England 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 as set out within NHS Digital guidance applicable to each data set.


DSfC - NHS Wakefield CCG - VAN — DARS-NIC-125783-W2W3P

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 - 'Other dissemination of 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 2018-04-01 — 2021-03-31 2019.03 — 2021.02.

Access method: Frequent Adhoc Flow, One-Off

Data-controller type: NHS WAKEFIELD CCG, NHS WAKEFIELD CCG, WAKEFIELD METROPOLITAN DISTRICT COUNCIL, NHS WEST YORKSHIRE ICB - 03R, NHS WEST YORKSHIRE ICB - 03R, WAKEFIELD METROPOLITAN DISTRICT COUNCIL

Sublicensing allowed: No

Datasets:

  1. Children and Young People Health
  2. Experience, Quality and Outcomes-Local Provider Flows
  3. Population Data-Local Provider Flows
  4. Acute-Local Provider Flows
  5. Improving Access to Psychological Therapies Data Set
  6. Civil Registration - Births
  7. Civil Registration - Deaths
  8. Primary Care Services-Local Provider Flows
  9. Maternity Services Data Set
  10. Ambulance-Local Provider Flows
  11. Community Services Data Set
  12. Community-Local Provider Flows
  13. Mental Health and Learning Disabilities Data Set
  14. Public Health and Screening Services-Local Provider Flows
  15. Demand for Service-Local Provider Flows
  16. Mental Health Minimum Data Set
  17. SUS for Commissioners
  18. Diagnostic Imaging Dataset
  19. Mental Health Services Data Set
  20. Diagnostic Services-Local Provider Flows
  21. Mental Health-Local Provider Flows
  22. Emergency Care-Local Provider Flows
  23. National Cancer Waiting Times Monitoring DataSet (CWT)
  24. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  25. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
  26. e-Referral Service for Commissioning
  27. National Diabetes Audit
  28. Patient Reported Outcome Measures
  29. Personal Demographic Service
  30. Summary Hospital-level Mortality Indicator
  31. Improving Access to Psychological Therapies Data Set_v1.5

Objectives:

Multi-specialty Community Provider (MCP) Vanguard
The primary objective for processing is to enable a robust evaluation of the MCP Vanguard interventions, in order to inform future service planning and resource allocation.

The primary activities within the vanguard will be establishing evening and weekend GP appointments, ensuring direct access to a physiotherapist for people with muscle and joint problems, having pharmacists work alongside health workers to make sure people get the right medicine, making use of video and email consultations, including the use of video technology to enable GPs and hospital clinicians to provide enhanced care in care homes, creating an electronic service directory and a wide range of apps to help people stay healthy and find the right service for them.

Using the data requested, the intention is to determine what impact the MCP Vanguard interventions are having on different elements of an individual’s care. This evidence will support future service delivery, but also provide the national new models of care team with information to enable them to determine the optimum service design that should be used for national roll out.

The main outcomes being looking at, will be the impact on secondary care activity, namely hospital admissions, A&E attendance, length of stay in hospital and whether an impact has been seen on the ambulance service regarding reduced demand, as many of the interventions are aimed at reducing this activity and subsequently the cost to the health system.


Enhanced Health Care Homes (EHCH) Vanguard
The primary objective for processing is to enable a robust evaluation of the Care Home Vanguard interventions, in order to information future service planning and resource allocation. This requires a dataset purely about the residents of care homes, and then linking their activity with several different services in order to understand the full spectrum of care that they receive.

The intention is to determine the impact the EHCH vanguard interventions are having on different elements of an individual’s care. This evidence will support future service delivery, but also provide the national new models of care team with information to enable them to determine the optimum design that should be used for national roll out.

The main outcomes being looking at will be the impact on secondary care activity, namely hospital admissions, A&E attendance, length of stay in hospital and whether an impact has been seen on the ambulance service regarding reduced demand, as many of the interventions are aimed at reducing this activity and subsequently the cost to the health system. Evaluation of whether the vanguard is impacting the ambulance service by seeing reduced demand and whether end of life care is improving.

The EHCH Vanguard will specifically relate to care home patients in the Wakefield locality and a number of schemes are specific to the EHCH vanguard. This will impact on the outcomes described above and evaluation will need to occur on these EHCH specific schemes. Therefore there is a need for two vanguards,. However, it should be mentioned that the EHCH vanguard is a subset of the MCP vanguard. The MCP schemes also has an impact on the EHCH vanguard outcomes, in addition to the EHCH schemes.

Expected Benefits:

MCP Vanguard

The information will allow the MCP and EHCH vanguards to understand the Health and Care need in an integrated manner. Showing areas of need that have not been highlighted previously in the area.
Understanding patient journeys in a more complete manner will allow the services to better plan and improve services to meet the need of the residents better.
It will allow understanding of the pinch point across the system between differing services. Showing which services are more effective at address need and help forecast the likely changing demands from the population.

EHCH Vanguard
The information will allow the MCP and EHCH vanguards to understand the Health and Care need in an integrated manner. Showing areas of need that have not been highlighted previously in the area.
Understanding patient journeys in a more complete manner will allow the services to better plan and improve services to meet the need of the residents better.
It will allow understanding of the pinch point across the system between differing services. Showing which services are more effective at address need and help forecast the likely changing demands from the population.

Outputs:

MCP Vanguard
End of year evaluation report. This will include analysis of the impacts that have been made on the following:
• Secondary care activity (admissions, A&E, bed days, ambulance service demand)
• Community services
• Mental Health services
Other outputs will be aggregated around individuals with specific conditions or service interventions they have received

EHCH Vanguard
End of year evaluation report. This will include analysis of the impacts that have been made on the following:
• Secondary care activity (admissions, A&E, bed days, ambulance service demand)
• Community services
• Mental Health services
• Mortality of care home residents
Other outputs will be aggregated around individuals with specific conditions or service interventions they have received
Specific to the EHCH vanguard, the majority of outputs will be aggregated, based around the care homes who are in scope and out of scope (over 500 residents in each cohort)
The data will also be used for monthly reporting against expected outcomes.

Processing:

Data must only be used as stipulated within this Data Sharing Agreement.
 
Data Processors must only act upon specific instructions from the Data Controller.
 
Data can only be stored at the addresses listed under storage addresses.
 
Patient level data will not be shared outside of the CCG unless it is for the purpose of Direct Care, where it may be shared only with those health professionals who have a legitimate relationship with the patient and a legitimate reason to access the data.
 
All access to data is managed under Roles-Based Access Controls
 
No patient level data will be linked other than as specifically detailed within this agreement. Data will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. The data to be released from NHS Digital will not be national data, but only that data relating to the specific locality and that data required by the applicant.
 
NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)
 
Segregation
Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.
 
All access to data is auditable by NHS Digital.


Data 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 -

• Patients who are normally registered and/or resident within the Wakefield CCG (including historical activity where the patient was previously registered or resident in another commissioner).
and/or
• Patients treated by a provider where Wakefield 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 Wakefield CCG - this is only for commissioning and relates to both national and local flows.


Calderdale and Huddersfield NHS Foundation Trust supply IT infrastructure and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Telecity, Yeadon Community Health Centre, Telstra, Pulsant, BDO and Engine 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.


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)

Data Processor 1 – North England Commissioning Support Unit

1) Data quality management and pseudonymisation of SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT) and Civil Registries Data (CRD) only is securely transferred from the DSCRO to North of England Commissioning Support Unit and the pseudonymised data is then held until completion of points 2 – 7.
2) North of England CSU also receive GP Data. It is received as follows:
a. Identifiable GP data is submitted to the CSU.
b. The data lands in a ring fenced area for GP data only.
c. There is a Data Processing Agreement in place between the GP practice and the CSU. A specific named individual within the CSU acts on behalf on the GP practice. This person has been issued with a black box.
d. The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to the pseudonymisation request. The individual does not have access to the data once it has been passed on to the CSU.
e. The GP data is then pseudonymised using the black box and DSCRO issued key – the clear data is then deleted from the ring fenced area.
f. The CSU are then sent the identifiable GP data with the pseudo key specific to the request.

3) North of England CSU also receive a pseudonymised flow of social care data from Wakefield Council . Social Care data is received as follows:
a. Wakefield Council is issued with their own black box solution.
b. Wakefield Council requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to Wakefield Council and the pseudonymisation request.
c. Wakefield Council submit the pseudonymised social care data to the CSU with the pseudo algorithm specific to them.
4) Once the pseudonymised GP data and/or social care data is received, the CSU make a request to the DSCRO.
5) The DSCRO send a mapping table to the CSU
6) The CSU overwrite the organisation specific keys with the DSCRO-provided CSU keys.
7) The mapping table is then deleted.
8) The DSCRO then pass the pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT) and Civil Registries Data (CRD) securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis.
9) Social care and/or GP data is then linked to the data sets listed within point 8 in the CSU
10) Aggregation of required data for CCG management use will be completed by the CSU as instructed by the CCG.
11) The linked pseudonymised data is securely passed to Data Processor 2 – eMBED and Data Processor 3 Wakefield Council and NHS Wakefield CCG.

Data Processor 2– Kier Business Services and Dr Foster (Hosting the eMBED Health Consortium)

12) North of England Commissioning Support Unit then securely send the pseudonymised and linked data to eMBED Health Consortium (hosted by Kier Business Services and Dr Foster). The eMBED Health Consortium analyse data to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
• Supporting the CCG with the development with its Primary Care Home Model of care, by understanding the population needs, demands and outcomes in depth for each of the primary care homes across the Wakefield system.
• Help shape commissioning processes to be place based, patient centred for health and social care providers locally.
• Support the system to evaluate interventions, services and projects.
b. Undertake population health management
• Provide insight and intelligence into the population needs and health and care demand for the Wakefield health and care system.
• As an example meeting districts recent strategic request to better understand, the complete patient experience of respiratory care pathways across the Wakefield system from health and social care providers.
c. Conduct Health Needs Assessments and thoroughly investigate the needs of the population
• Articulate the changing levels of population need for health and care services for respiratory care, again as an recent example.
• Support the local Joint Strategic needs Assessment Process, by provider more complete understanding of population need from their conditions and journeys through care pathways across the Wakefield system.
d. Understand cohorts of residents who are at risk
• Implement existing models of risk and approaches to segmentation in line with the Population Health Management approach being rolled out by NHS E
• Develop local risk models and predictive analytics for support preventative activity.

13) eMBED Health Consortium (hosted by Kier Business Services and Dr Foster) then pass the processed, pseudonymised and linked data to Wakefield Council and the CCG.

Data Processor 3 - Wakefield Council

14) Wakefield Council analyse data to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
• Supporting the CCG with the development with its Primary Care Home Model of care, by understanding the population needs, demands and outcomes in depth for each of the primary care homes across the Wakefield system.
• Help shape commissioning processes to be place based, patient centred for health and social care providers locally.
• Support the system to evaluate interventions, services and projects.
b. Undertake population health management
• Provide insight and intelligence into the population needs and health and care demand for the Wakefield health and care system.
• As an example meeting districts recent strategic request to better understand, the complete patient experience of respiratory care pathways across the Wakefield system from health and social care providers.
c. Conduct Health Needs Assessments and thoroughly investigate the needs of the population
• Articulate the changing levels of population need for health and care services for respiratory care, again as an recent example.
• Support the local Joint Strategic needs Assessment Process, by provider more complete understanding of population need from their conditions and journeys through care pathways across the Wakefield system.
d. Understand cohorts of residents who are at risk
• Implement existing models of risk and approaches to segmentation in line with the Population Health Management approach being rolled out by NHS England.
• Develop local risk models and predictive analytics for support preventative activity.

15). Wakefield Council then pass the processed, pseudonymised and linked data to the CCG.

16) Aggregation of required data for CCG management use will be completed by eMBED Health Consortium (hosted by Kier Business Services and Dr Foster), Wakefield Council or the CCG as instructed by the CCG.

17) Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.