DSfC - NHS East Berkshire CCG, NHS North East Hampshire and Farnham CCG and NHS Surrey Heath CCG; STP, Comm

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 CCGs 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 CCGs are part of the Frimley Health Sustainable Transformation Partnership. The STP is responsible for implementing large parts of the 5 year forward view from NHS England. The STP is implementing several initiatives:

- Putting the patient at the heart of the health system

- Working across organisational boundaries to deliver care and including social care, public Health, providers and GPs as well as CCGs

- Reviewing patient pathways to improve patient experience whilst reducing costs e.g. reduce the number of standard tests a patient may have and only have the ones they need

- Planning the demand and capacity across the healthcare system across 3 CCGs to ensure we have the right buildings, services and staff to cope with demand whilst reducing the impact on costs

- Working to prevent or capture conditions early as they are cheaper to treat

- Introduce initiatives to change behaviours e.g. move more care into the community

- Patient pathway planning for the above

To ensure the patient is at the heart of care, the STP is focussing on where services are required across the geographical region. This assists to ensure delivery of care in the right place for patients who may move and change services across CCGs.

The CCGs will work proactively and collaboratively with the other CCGs in the STP to redesign services across boundaries to integrate services. Collaborative sharing is required for CCGs to understand these requirements.

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 (NCWT)

- Civil Registries Data (CRD) (Births and Deaths)

The pseudonymised data is required to for the following purposes:

- Population health management:

- Understanding the interdependency of care services

- Targeting care more effectively

- Using value as the redesign principle

- Ensuring we do what we should

- Data Quality and Validation – allowing data quality checks on the submitted data

- Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them

- Understanding cohorts of residents who are at risk of becoming users of some of the more expensive services, to better understand and manage those needs

- Monitoring population health and care interactions to understand where people may slip through the net, or where the provision of care may be being duplicated

- Modelling activity across all data sets to understand how services interact with each other, and to understand how changes in one service may affect flows through another

- Service redesign

- Health Needs Assessment – identification of underlying disease prevalence within the local population

- Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls, computed using algorithms executed against linked de-identified data, and identification of future service delivery models

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

Processing for commissioning will be conducted by

- South, Central and West Commissioning Support Unit

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

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

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

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

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

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

Onward Sharing

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

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

Segregation

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

All access to data is auditable by NHS Digital.

Data Minimisation

For the purpose of Commissioning:

• Patients who are normally registered and/or resident within the CCGs (NHS East Berkshire CCG, NHS North East Hampshire and Farnham CCG and NHS Surrey Heath CCG) (including historical activity where the patient was previously registered or resident in another commissioner).

and/or

• Patients treated by a provider where the CCGs (NHS East Berkshire CCG, NHS North East Hampshire and Farnham CCG and NHS Surrey Heath CCG) 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 (NHS East Berkshire CCG, NHS North East Hampshire and Farnham CCG and NHS Surrey Heath CCG) - this is only for commissioning and relates to both national and local flows.

University Hospitals Bristol NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Black Box Software

- The Black Box is a software process with very limited access, restricted to only those who administer it.

- It is a set of logic that is hidden from users. It generates a re-pseudonymised output from the data that users enter.

- The purpose of the Black Box is to map the data such that the resulting pseudonymisation is the same as that used at the DSCRO.

- The Black Box works by calling upon a mapping table from the DSCRO and re-pseudonymising by switching the pseudonym. No data is persisted in the Black Box.

The Black Box is held within a private part of South Central and West Commissioning Support Unit secure network and physically located at the storage address within the DARS application/agreement with the same underlying security controls.)

Commissioning

The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:

1. SUS

2. Local Provider Flows (received directly from providers)

o Acute

o Ambulance

o Community

o Demand for Service

o Diagnostic Service

o Emergency Care

o Experience, Quality and Outcomes

o Mental Health

o Other Not Elsewhere Classified

o Population Data

o Primary Care Services

o Public Health Screening

3. Mental Health Minimum Data Set (MHMDS)

4. Mental Health Learning Disability Data Set (MHLDDS)

5. Mental Health Services Data Set (MHSDS)

6. Maternity Services Data Set (MSDS)

7. Improving Access to Psychological Therapy (IAPT)

8. Child and Young People Health Service (CYPHS)

9. Community Services Data Set (CSDS)

10. Diagnostic Imaging Data Set (DIDS)

11. National Cancer Waiting Times (NCWT)

12. Civil Registries Data (CRD)

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

Data Processor 1 - South, Central and West Commissioning Support Unit

1. Pseudonymised SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times (NCWT), Civil Registries Data (CRD) and Diagnostic Imaging data (DIDS) only is held until points 2 – 8 are completed.

2. South, Central and West Commissioning Support Unit receives GP data. GP Data is received as follows:

o Identifiable GP data is submitted to South Central and West Commissioning Support Unit.

o The identifiable data lands in a ring-fenced area for GP data only.

o The GP data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.

o There is a Data Processing Agreement in place between the GP and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the GP.

o This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.

o Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.

o South Central and West Commissioning Support Unit are then sent the pseudonymised GP data with the pseudo algorithm specific to them.

3. South, Central and West Commissioning Support Unit also receive a flow of social care data. Social Care data is received in one of the following 2 ways:

o Pseudonymised:

 Social Care data is pseudonymised within the provider using a pseudonymisation tool, different to that used by the DSCRO. The provider requests a pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the Local Authority and to that specific date.

 The pseudonymised data lands in a ring-fenced area for social care data only.

 There is a Data Processing Agreement in place between the Provider and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the Provider.

 This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.

 The data is then passed into the non-ringfenced area with the pseudo algorithm specific to them.

o Identifiable:

 Identifiable social care data is submitted to South Central and West Commissioning Support Unit.

 The identifiable data lands in a ring-fenced area for social care data only.

 The social care data is pseudonymised using a pseudonymisation tool, different to that used by the DSCRO.

 There is a Data Processing Agreement in place between the Local Authority and South Central and West Commissioning Support Unit. A specific named individual within South Central and West Commissioning Support Unit acts on behalf of the provider.

 This individual has access to a black box. The pseudonymised data is passed through the black box process where the pseudonymisation is mapped to the pseudonymisation used by the DSCRO.

 Once mapped, the data is passed into South Central and West Commissioning Support, but before South Central and West Commissioning Support Unit will receive the data from the ring-fenced area, they require confirmation that the identifiable data has been deleted.

 South Central and West Commissioning Support Unit are then sent the pseudonymised social care data with the pseudo algorithm specific to them.

4. Once the pseudonymised GP data and social care data is received, South, Central and West Commissioning Support Unit make a request to the DSCRO.

5. The DSCRO check the dates of the key generation (Point 2d and 3aii/3biv).

6. The DSCRO then send a mapping table to South, Central and West Commissioning Support Unit

7. South, Central and West Commissioning Support Unit then overwrite the organisation specific keys with the DSCRO key.

8. The mapping table is then deleted.

9. The DSCRO pass the pseudonymised SUS, local provider data, Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS), Community Services Data Set (CSDS), National Cancer Waiting Times (NCWT), Civil Registries Data (CRD) and Diagnostic Imaging (DIDS) securely to South, Central and West Commissioning Support Unit for the addition of derived fields, linkage of data sets and analysis

10. GP and Social care data is then linked to the data sets listed within point 9.

11. South, Central and West Commissioning Support Unit then pass the processed, pseudonymised and linked data to the CCG.

12. Aggregation of required data for CCG management use will be completed by South, Central and West Commissioning Support Unit as instructed by the CCG.

13. 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.

Commissioning

1. Commissioner reporting:

a. Summary by provider view - plan & actuals year to date (YTD).

b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.

c. Summary by provider view - activity & finance variance by POD.

d. Planned care by provider view - activity & finance plan & actuals YTD.

e. Planned care by POD view - activity plan & actuals YTD.

f. Provider reporting.

g. Statutory returns.

h. Statutory returns - monthly activity return.

i. Statutory returns - quarterly activity return.

j. Delayed discharges.

k. Quality & performance referral to treatment reporting.

2. Readmissions analysis.

3. Production of aggregate reports for CCG Business Intelligence.

4. Production of project / programme level dashboards.

5. Monitoring of acute / community / mental health quality matrix.

6. Clinical coding reviews / audits.

7. Budget reporting down to individual GP Practice level.

8. GP Practice level dashboard reports include high flyers.

9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports

10. Data Quality and Validation measures allowing data quality checks on the submitted data

11. Contract Management and Modelling

12. Patient Stratification, such as:

o Patients at highest risk of admission

o Most expensive patients (top 15%)

o Frail and elderly

o Patients that are currently in hospital

o Patients with most referrals to secondary care

o Patients with most emergency activity

o Patients with most expensive prescriptions

o Patients recently moving from one care setting to another

i. Discharged from hospital

ii. Discharged from community

13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.

14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.

15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.

16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.

17. Removal of patients from Risk Stratification reports.

18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.

19. Profiling population health and wider determinants to identify and target those most in need

a. Understanding population profile and demographics

b. Identify patient cohorts with specific needs or who may benefit from interventions

c. Identifying disease prevalence. health and care needs for population cohorts

d. Contributing to Joint Strategic Needs Assessment (JSNA)

e. Geographical mapping and analysis

20. Identifying and managing preventable and existing conditions

a. Identifying types of individuals and population cohorts at risk of non-elective re-admission

b. Risk stratification to identify populations suitable for case management

c. Risk profiling and predictive modelling

d. Risk stratification for planning services for population cohorts

e. Identification of disease incidence and diagnosis stratification

21. Reducing health inequalities

a. Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs

b. Socio-demographic analysis

22. Managing demand

a. Waiting times analysis

b. Service demand and supply modelling

c. Understanding cross-border and overseas visitor

d. Winter planning

e. Emergency preparedness, business continuity, recovery and contingency planning

23. Care co-ordination and planning

a. Planning packages of care

b. Service planning

c. Planning care co-ordination

24. Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system

a. Patient pathway analysis across health and care

b. Outcomes & experience analysis

c. Analysis to support anti-terror initiatives

d. Analysis to identify vulnerable patients with potential safeguarding issues

e. Understanding equity of care and unwarranted variation

f. Modelling patient flow

g. Tracking patient pathways

h. Monitoring to support NMoC, ACOs, STPs

i. Identifying duplications in care

j. Identifying gaps in care, missed diagnoses and triple fail events

k. Analysing individual and aggregated timelines

25. Undertaking budget planning, management and reporting

a. Tracking financial performance against plans

b. Budget reporting

c. Tariff development

d. Developing and monitoring capitated budgets

e. Developing and monitoring individual-level budgets

f. Future budget planning and forecasting

g. Paying for care of overseas visitors and cross-border flow

26. Monitoring the value for money

a. Service-level costing & comparisons

b. Identification of cost pressures

c. Cost benefit analysis

d. Equity of spend across services and population cohorts

e. Finance impact assessment

27. Comparing population groups, peers, national and international best practice

a. Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice

b. Benchmarking against other parts of the country

c. Identifying unwarranted variations

28. Comparing expected levels

a. Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations

29. Comparing local targets & plan

a. Monitoring of local variation in productivity, cost, outcomes, quality and experience

b. Local performance dashboards by service provider, commissioner, geography, NMOC, STPs

30. Monitoring activity and cost compliance against contract and agreed plans

a. Contract monitoring

b. Contract reconciliation and challenge

c. Invoice validation

31. Monitoring provider quality, demand, experience and outcomes against contract and agreed plans

a. Performance dashboards

b. CQUIN reporting

c. Clinical audit

d. Patient experience surveys

e. Demand, supply, outcome & experience analysis

f. Monitoring cross-border flows and overseas visitor activity

32. Improving provider data quality

a. Coding audit

b. Data quality validation and review

c. Checking validity of patient identity and commissioner assignment

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. Reviewing current service provision

a. Cost-benefit analysis and service impact assessments to underpin service transformation across health economy

b. Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.)

c. Impact analysis for different models or productivity measures, efficiency and experience

d. Service and pathway review

e. Service utilisation review

19. Ensuring compliance with evidence and guidance

a. Testing approaches with evidence and compliance with guidance.

20. Monitoring outcomes

a. Analysis of variation in outcomes across population group

21. Understanding how services impact across the health economy

a. Service evaluation

b. Programme reviews

c. Analysis of productivity, outcomes, experience, plan, targets and actuals

d. Assessing value for money and efficiency gains

e. Understanding impact of services on health inequalities

22. Understanding how services impact on the health of the population and patient cohorts

a. Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this

b. Propensity matching and scoring

c. Triple aim analysis

23. Understanding future drivers for change across health economy

a. Forecasting health and care needs for population and population cohorts across STPs

b. Identifying changes in disease trends and prevalence

c. Efficiencies that can be gained from procuring services across wider footprints, from new innovations

d. Predictive modelling

24. Delivering services that meet changing needs of population

a. Analysis to support policy development

b. Ethical and equality impact assessments

c. Implementation of NMOC

d. What do next years contracts need to include?

e. Workforce planning

25. Maximising services and outcomes within financial envelopes across health economy

a. What-if analysis

b. Cost-benefit analysis

c. Health economics analysis

d. Scenario planning and modelling

e. Investment and disinvestment in services analysis

f. Opportunity analysis

Not stated in the register.