NHS Digital Data Release Register - reformatted

NHS Blackburn With Darwen CCG projects

1005 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).


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

DSfC Template 22 — DARS-NIC-580892-L7J0N

Opt outs honoured: Anonymised - ICO Code Compliant

Legal basis: Health and Social Care Act 2012 - s261 - 'Other dissemination of information'

Purposes: (Clinical Commissioning Group (CCG))

Sensitive: Sensitive

When:DSA runs 2021-11-11 — 2024-11-10

Access method: Frequent Adhoc Flow

Data-controller type: NHS BLACKBURN WITH DARWEN CCG, NHS BLACKPOOL CCG, NHS CHORLEY AND SOUTH RIBBLE CCG, NHS EAST LANCASHIRE CCG, NHS FYLDE AND WYRE CCG, NHS GREATER PRESTON CCG, NHS MORECAMBE BAY CCG, NHS WEST LANCASHIRE CCG

Sublicensing allowed: No

Datasets:

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

Yielded Benefits:

No Yielded Benefits can be evidenced as data has not yet been processed for the purposes in this DSA

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.
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 opposed to only those that engage with services
24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice.
25. Monitor the quality and safety of the delivery of healthcare services.
26. Allow focused commissioning support based on factual data rather than assumed and projected sources
27. Understand admissions linked to overprescribing.
28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification.
29. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care
30. Designing and implementing new payment models across health and adult social care
31. Understanding current and future population needs and resource utilisation for local strategic planning and commissioning purposes including for health, social care and public health needs.

Meridian Productivity Limited
Understand site & service consolidation opportunities across Lancashire & South Cumbria (L&SC) ICS as part of the ICS development programme for ophthalmology services. Ophthalmology services span across multiple acute and community providers in L&SC. As part of ICS development (integrating the services across the eight CCGs in the geography) there is a need to understand which sites and services are most effective at delivering and satisfying the health needs of the population. Once this is understood the ICS can look to consolidate sites & services where it is beneficial to do so (without impacting population health, travel, service quality, workforce, financials etc). This modelling will provide a balanced view of each site/ service and develop a list of options to consider - which sites & services to integrate/ consolidate. This will enable the ICS to develop their Ophthalmology services in a balanced and data-driven manner.

Outputs:

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
15. The addition of Mental Health Services Data Set enriches the data available and will help GPs identify and prevent mental health patients from needing urgent hospital care and / or being admitted to a psychiatric hospital
In addition:
- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.

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

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:
There is no requirement for the analytical teams to re-identify patients, but in the development of cohorts of patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct healthcare professionals or local authority direct care staff only for the purpose of direct care. Additionally clinicians, made aware of a number of cases that they believe would need intervention may request re-identification for that direct care purpose.

These instances of re-identification will generally be carried out as programmes of work or, rarely, on an individual/small group basis. All re-id requests will be processed and authorised by the DSCRO on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.

The following are typical examples of instances where a CCG might want use the re-identification process:

A&E High Attendance usage
The CCG can filter data to show for example the number of A&E attendances in a given period for each patient. The CCG can then flag to the relevant GP of the patient any patients that require intervention. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk.

Polypharmacy re-IDs
CCG's can request re-ID of a list of patients to be sent to the relevant GP with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.

The Re-identification process for direct care is as follows:
1. The CCG identifies a patient cohort to be re-identified for the purpose of direct care.
2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSU’s Business Intelligence (BI) Tool, or through a manual form.
3. The DSCRO assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data. These checks are carried out either by DSCRO staff using pre-approved information (timing’s, requester’s identity etc) or via an automated system.
4. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.
5. DSCROs retain an audit trail of all re-id requests
6. National Data opt outs are not applied for the purpose of direct care

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

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)
16. e-Referral Service (eRS)
17. Personal Demographics Service (PDS)
18. Summary Hospital-level Mortality Indicator (SHMI)
19. Medicines Dispensed in Primary Care (NHSBSA Data)
20. Adult Social Care Data

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

Data Processor 1 – NHS Midlands and Lancashire Commissioning Support Unit
1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS), Summary Hospital-level Mortality Indicator (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data only is securely transferred from the DSCRO to NHS Midlands and Lancashire Commissioning Support Unit.
2. NHS Midlands and Lancashire 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. NHS Midlands and Lancashire 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 NHS Midlands and Lancashire 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.

Data Processor 2 – Meridian Productivity Limited
1. Pseudonymised SUS+ data only is securely transferred from NHS Midlands and Lancashire Commissioning Support Unit to Meridian Productivity Limited.
2. Meridian Productivity Limited utilise the data to:
• undertake a review of Lancashire and South Cumbria SUS data to support future requirements around ophthalmology services
4. Meridian Productivity Limited then pass the processed, pseudonymised and linked data to the CCGs.
5. Aggregation of required data for CCG management use will be completed by Meridian Productivity Limited or the CCGs as instructed by the CCGs.
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 Blackburn & Darwen CCG- IV, RS, Comm — DARS-NIC-41477-N2G4S

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld, Anonymised - ICO Code Compliant, Identifiable (Does not include the flow of confidential data, Mixture of confidential data flow(s) with consent and flow(s) with support under section 251 NHS Act 2006, 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), 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 - 'Other dissemination of information', Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 – s261(7), Health and Social Care Act 2012 – s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: (Clinical Commissioning Group (CCG))

Sensitive: Sensitive

When:2018.06 — 2021.05. DSA runs 2019-05-02 — 2022-05-01

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

Data-controller type: NHS BLACKBURN WITH DARWEN CCG

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. Civil Registration - Births
  22. Civil Registration - Deaths
  23. Community Services Data Set
  24. National Cancer Waiting Times Monitoring DataSet (CWT)
  25. National Diabetes Audit
  26. Patient Reported Outcome Measures
  27. e-Referral Service for Commissioning
  28. Personal Demographic Service
  29. Summary Hospital-level Mortality Indicator
  30. National Cancer Waiting Times Monitoring DataSet (NCWTMDS)

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 pseudonymised.
Invoice Validation with be conducted by Midlands and Lancashire Commissioning Support Unit.
The CCG are advised by Midlands and Lancashire 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 focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.
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 Midlands and Lancashire Commissioning Support Unit.

Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- 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 Midlands and Lancashire Commissioning Support Unit.

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
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)

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

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

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

All access to data is auditable by NHS Digital.

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

Invoice Validation
1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and pseudonymisation is completed within the DSCRO and the data is then sent to the Controlled Environment for Finance (CEfF) in Midlands and Lancashire Commissioning Support Unit.
3. Midlands and Lancashire Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance. 
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between Midlands and Lancashire 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 Midlands and Lancashire Commissioning Support Unit, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Midlands and Lancashire Commissioning Support Unit.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Midlands and Lancashire Commissioning Support Unit has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.

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. Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – Midlands and Lancashire 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 Midlands and Lancashire Commissioning Support Unit.
2. Midlands and Lancashire 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. Midlands and Lancashire 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 Midlands and Lancashire 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.


Project 3 — DARS-NIC-147840-N7W5C

Opt outs honoured: No - data flow is not identifiable, Yes - patient objections upheld (Section 251)

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

Purposes: ()

Sensitive: Sensitive

When:2018.10 — 2019.04. DSA runs —

Access method: Frequent Adhoc Flow

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Acute-Local Provider Flows
  2. Ambulance-Local Provider Flows
  3. Children and Young People Health
  4. Community Services Data Set
  5. Community-Local Provider Flows
  6. Demand for Service-Local Provider Flows
  7. Diagnostic Imaging Dataset
  8. Diagnostic Services-Local Provider Flows
  9. Emergency Care-Local Provider Flows
  10. Experience, Quality and Outcomes-Local Provider Flows
  11. Improving Access to Psychological Therapies Data Set
  12. Maternity Services Data Set
  13. Mental Health and Learning Disabilities Data Set
  14. Mental Health Minimum Data Set
  15. Mental Health Services Data Set
  16. Mental Health-Local Provider Flows
  17. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  18. Population Data-Local Provider Flows
  19. Primary Care Services-Local Provider Flows
  20. Public Health and Screening Services-Local Provider Flows
  21. SUS for Commissioners

Objectives:

Risk Stratification
Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides 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 Midlands and Lancashire Commissioning Support Unit

Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Community Services Data Set (CSDS)
- Diagnostic Imaging Data Set (DIDS)
- National Cancer Waiting Times Monitoring Data Set (CWT)

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 Midlands and Lancashire Commissioning Support Unit

Expected Benefits:

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

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 and that data required by 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 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.




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 Midlands and Lancashire Commissioning Support Unit, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Midlands and Lancashire Commissioning Support Unit.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Midlands and Lancashire Commissioning Support Unit has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Community Services Data Set (CSDS)
10. Diagnostic Imaging Data Set (DIDS)
11. National Cancer Waiting Times Monitoring Data Set (CWT)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – Midlands and Lancashire 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) and National Cancer Waiting Times Monitoring Data Set (CWT) only is securely transferred from the DSCRO to Midlands and Lancashire Commissioning Support Unit.
2. Midlands and Lancashire 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. Midlands and Lancashire 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 Midlands and Lancashire 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.


Project 4 — NIC-41477-N2G4S

Opt outs honoured: N, Y ()

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

Purposes: ()

Sensitive: Sensitive

When:2017.09 — 2017.05. DSA runs —

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

  1. Local Provider Data - Acute
  2. Local Provider Data - Demand For service
  3. Improving Access to Psychological Therapies Data Set
  4. Mental Health Minimum Data Set
  5. SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
  6. SUS for Commissioners
  7. Public Health and Screening Services-Local Provider Flows
  8. Primary Care Services-Local Provider Flows
  9. Population Data-Local Provider Flows
  10. Other Not Elsewhere Classified (NEC)-Local Provider Flows
  11. Mental Health-Local Provider Flows
  12. Mental Health Services Data Set
  13. Mental Health and Learning Disabilities Data Set
  14. Maternity Services Data Set
  15. Experience, Quality and Outcomes-Local Provider Flows
  16. Emergency Care-Local Provider Flows
  17. Diagnostic Services-Local Provider Flows
  18. Diagnostic Imaging Dataset
  19. Demand for Service-Local Provider Flows
  20. Community-Local Provider Flows
  21. Children and Young People Health
  22. Ambulance-Local Provider Flows
  23. Acute-Local Provider Flows
  24. SUS (Accident & Emergency, Inpatient and Outpatient data)
  25. Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Primary Care
  26. Children and Young People's Health Services Data Set
  27. Local Provider Data - Ambulance
  28. Local Provider Data - Community
  29. Local Provider Data - Diagnostic Services
  30. Local Provider Data - Emergency Care
  31. Local Provider Data - Mental Health
  32. Local Provider Data - Primary Care
  33. SUS Accident & Emergency data
  34. SUS Admitted Patient Care data
  35. SUS Outpatient data

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number to undertake invoice validation on behalf of the CCG. In order to support commissioning of patient care by validating non-contracted activity in the CCG, this data is required for the purpose of invoice validation. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF.

Risk Stratification
This is an application to use SUS data identifiable at the level of NHS number for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users.

Pseudonymised – SUS and Local Flows
Application for the CCG to use pseudonymised data to provide intelligence to support commissioning of health services. The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
Application for the CCG to use MHSDS, MHMDS, MHLDDS, MSDS, IAPT, CYPHS and DIDs linked and pseudonymised data to provide intelligence to support commissioning of health services. The linked, pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets.


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

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 misapproproation of public funds to ensure the on-going 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 and early intervention of appropriate care.
3) Improved access to services by identifying which services may be in demand but have poor access, and from this identify areas where improvement is required.
4) Potentially reduced premature mortality by more targeted intervention in primary care, which supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework.
5) Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.

Pseudonymised – SUS and Local Flows
1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways.
2) Health economic modelling using:
a) Analysis on provider performance against 18 weeks wait targets
b) Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients
c) Analysis of outcome measures for differential treatments, accounting for the full patient pathway
d) Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC) flows
3) Commissioning cycle support for grouping and re-costing previous activity
4) Enables monitoring of:
a) CCG outcome indicators
b) Non-financial validation of patient level data
c) Successful delivery of integrated care within the CCG
d) Checking frequent or multiple attendances to improve early intervention and avoid admissions
e) Commissioning and performance management
5) Feedback to NHS service providers on data quality at an aggregate level

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
1) Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management and pathways.
2) Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types.
3) Health economic modelling using:
(a) Analysis on provider performance.
(b) Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients.
(c) Analysis of outcome measures for differential treatments, accounting for the full patient pathway.
4) Commissioning cycle support for grouping and re-costing previous activity.
5) Enables monitoring of:
(a) CCG outcome indicators.
(b) Non-financial validation of activity.
(c) Successful delivery of integrated care within the CCG.
(d) Checking frequent or multiple attendances to improve early intervention and avoid admissions.
(e) Case management.
(f) Care service planning.
(g) Commissioning and performance management.
(h) List size verification by GP practices.
(i) Understanding the care of patients in nursing homes.
6) Feedback to NHS service providers on data quality at an aggregate and individual record level.

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 with no identifiers

3) Record level output will be available for commissioners in anonymised or pseudonymised format.

4) GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.

Pseudonymised – SUS and Local Flows
1) Commissioner reporting:
(a) Summary by provider view - plan & actuals year to date (YTD).
(b) Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
(c) Summary by provider view - activity & finance variance by POD.
(d) Planned care by provider view - activity & finance plan & actuals YTD.
(e) Planned care by POD view - activity plan & actuals YTD.
(f) Provider reporting.
(g) Statutory returns.
(h) Statutory returns - monthly activity return.
(i) Statutory returns - quarterly activity return.
(j) Delayed discharges.
(k) Quality & performance referral to treatment reporting.
2) Readmissions analysis.
3) Production of aggregate reports for CCG Business Intelligence.
4) Production of project / programme level dashboards.
5) Monitoring of acute / community / mental health quality matrix.
6) Clinical coding reviews / audits.
7) Budget reporting down to individual GP Practice level.
8) GP Practice level dashboard reports include high flyers.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
1) Commissioner reporting:
(a) Summary by provider view - plan & actuals year to date (YTD).
(b) Summary by Patient Outcome Data (POD) view - plan & actuals YTD.
(c) Summary by provider view - activity & finance variance by POD.
(d) Planned care by provider view - activity & finance plan & actuals YTD.
(e) Planned care by POD view - activity plan & actuals YTD.
(f) Provider reporting.
(g) Statutory returns.
(h) Statutory returns - monthly activity return.
(i) Statutory returns - quarterly activity return.
(j) Delayed discharges.
(k) Quality & performance referral to treatment reporting.
2) Readmissions analysis.
3) Production of aggregate reports for CCG Business Intelligence.
4) Production of project / programme level dashboards.
5) Monitoring of acute / community / mental health quality matrix.
6) Clinical coding reviews / audits.
7) Budget reporting down to individual GP Practice level.

Processing:

Central Midlands DSCRO will apply Type 2 objections (from 1st October 2016 onwards) before any identifiable data leaves the DSCRO.
Invoice Validation
1) Central and Midlands DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the Midlands and Lancashire CSU (Data Processor 1).

2) The CSU carry out the following processing activities within the CEfF for invoice validation purposes:

a) Checking the individual is registered to a particular Clinical Commissioning Group (CCG) by using the derived commissioner field in SUS and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow

b) Once the backing information is received, this will be checked against system access and reports provided by the HSCIC to confirm the payments are:
- In line with Payment by Results tariffs
- are in relation to a patient registered with a CCG GP or resident within the CCG area.
- The health care provided should be paid by the CCG in line with CCG guidance. 
3) The CCG are notified of that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the CSU and the provider meaning that no data needs to be sent to the CCG. The CCG only receives notification to pay.

Risk Stratification
1) SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from Central and Midlands Data Services for Commissioners Regional Office (DSCRO) to the data processor.
2) Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to Midlands and Lancashire CSU (Data Processor 1), who hold the SUS data within the secure Data Centre on N3.
3) SUS data is linked to GP data in the risk stratification tool by the data processor.
4) As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
5) Midlands and Lancashire CSU who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
6) Once Midlands and Lancashire CSU has completed the processing, the CCG can dial in to the online system via N3 connection to access the data anonymised at patient level.

Pseudonymised – SUS and Local Flows
1) Central and Midlands Data Services for Commissioners Regional Office (DSCRO) receives a flow of SUS identifiable data for the CCG from the SUS Repository. Central and Midlands DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2) Data quality management of data is completed by the DSCRO and the identifiable data is then passed securely to North England CSU for the addition of derived fields, linkage of data sets and analysis.
3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4) Patient level data will not be shared outside of the CCG. External aggregated reports only.

Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1) Central and Midlands Data Services for Commissioning Regional Office (DSCRO) will receive a flow of pseudonymised patient level data for each CCG for Mental Health (MHSDS, MHMDS, MHLDDS), Improving Access to Psychological Therapies (IAPT), Maternity (MSDS), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes
2) Data quality management of data is completed by the DSCRO and the pseudonymised data is then passed securely to Midlands and Lancashire CSU for the addition of derived fields, linkage of data sets and analysis. Linkage is not with other datasets just between the data contained within the dataset itself.
3) Midlands and Lancashire CSU then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4) The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5) The CCG completes aggregation of required data for CCG management use – disclosing any outputs at the appropriate level.
6) Patient level data will not be shared outside of the CCG. External aggregated reports only with small numbers suppressed with HSCIC guidance.