DSfC - NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG - Comm

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

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

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

The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:

- Secondary Uses Service (SUS+)

- Local Provider Flows

o Acute

o Ambulance

o Community

o Demand for Service

o Diagnostic Service

o Emergency Care

o Experience, Quality and Outcomes

o Mental Health

o Other Not Elsewhere Classified

o Population Data

o Primary Care Services

o Public Health Screening

- Mental Health Minimum Data Set (MHMDS)

- Mental Health Learning Disability Data Set (MHLDDS)

- Mental Health Services Data Set (MHSDS)

- Maternity Services Data Set (MSDS)

- Improving Access to Psychological Therapy (IAPT)

- Child and Young People Health Service (CYPHS)

- Community Services Data Set (CSDS)

- Diagnostic Imaging Data Set (DIDS)

- National Cancer Waiting Times Monitoring Data Set (CWT)

- Civil Registries Data (CRD) (Births)

- Civil Registries Data (CRD) (Deaths)

- National Diabetes Audit (NDA)

- Patient Reported Outcome Measures (PROMs)

The pseudonymised data is required for the following purposes:

 Population health management:

• Understanding the interdependency of care services

• Targeting care more effectively

• Using value as the redesign principle

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

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

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

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

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

 Service redesign

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

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

The pseudonymised data is required to ensure that analysis of health care provision can be completed to support the needs of the health profile of the population within the CCGs' areas based on the full analysis of multiple pseudonymised datasets. The added GP linkage will enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.

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

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

PROCESSING CONDITIONS

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

Data Processors must only act upon specific instructions from their relevant Data Controller and may only process data under instruction from the CCG which they have a processing agreement in place with:

NHS Bedfordshire CCG – South, Central and West Commissioning Support Unit

NHS Luton CCG – North East London Commissioning Support Unit

NHS Milton Keynes CCG – Arden and GEM Commissioning Support Unit

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

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

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

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

ONWARD SHARING:

Patient level data will not be shared outside of the data controllers. Re-identification of data is not permitted under this agreement.

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

SEGREGATION:

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

All access to data is auditable by NHS Digital.

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

NHS Bedfordshire CCG – NHS South, Central and West Commissioning Support Unit

NHS Luton CCG – NHS North East London Commissioning Support Unit

NHS Milton Keynes CCG – NHS Arden and GEM Commissioning Support Unit

For population health management purposes NHS North East London Commissioning Support Unit will be processing data on behalf of the NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG.

For population health management purposes NHS North East London Commissioning Support Unit will be processing data on behalf of NHS Arden & Greater Eastern Midlands Commissioning Support Unit and NHS South Central and West Commissioning Support Unit.

DATA MINIMISATION

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

• Patients who are normally registered and/or resident within the CCG region (including historical activity where the patient was previously registered or resident in another commissioner).

and/or

• Patients treated by a provider where CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows.

and/or

• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of CCG - this is only for commissioning and relates to both national and local flows.

Microsoft Limited provide cloud services for NHS North East London Commissioning Support Unit, NHS Arden and Greater Eastern Midlands Commissioning Support Unit, NHS Midlands and Lancashire Commissioning Support Unit and NHS South, Central and West Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the databases containing the data.

Amazon Web Services provide cloud services for Optum Health Solutions UK Ltd and are therefore listed as a data processor. They supply support to the system but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the databases containing the data.

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

University Hospitals Bristol NHS Foundation Trust, Ilkeston Community Hospital (Part of Derbyshire Community Health Services NHS Foundation Trust) and Wrightington, Wigan and Leigh NHS Foundation Trust do not access data held under this agreement as they only supply the building. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data. Interxion are tasked with running a simple backup process alongside providing the building. They also do not access the data but have been included in the Processing addresses for clarity.

NHS Digital will securely transfer the following minimised and pseudonymised datasets to the respective Commissioning Support Unit:

1. SUS+

2. Local Provider Flows (received directly from providers)

a. Acute

b. Ambulance

c. Community

d. Demand for Service

e. Diagnostic Service

f. Emergency Care

g. Experience, Quality and Outcomes

h. Mental Health

i. Other Not Elsewhere Classified

j. Population Data

k. Primary Care Services

l. Public Health Screening

3. Mental Health Minimum Data Set (MHMDS)

4. Mental Health Learning Disability Data Set (MHLDDS)

5. Mental Health Services Data Set (MHSDS)

6. Maternity Services Data Set (MSDS)

7. Improving Access to Psychological Therapy (IAPT)

8. Child and Young People Health Service (CYPHS)

9. Community Services Data Set (CSDS)

10. Diagnostic Imaging Data Set (DIDS)

11. National Cancer Waiting Times Monitoring Data Set (CWT)

12. Civil Registries Data (CRD) (Births)

13. Civil Registries Data (CRD) (Deaths)

14. National Diabetes Audit (NDA)

15. Patient Reported Outcome Measures (PROMs)

Each Commissioning Support Unit link data and provide analysis to:

a. See patient journeys for pathways or service design, re-design and de-commissioning.

b. Check recorded activity against contracts or invoices and facilitate discussions with providers.

c. Undertake population health management

d. Undertake data quality and validation checks

e. Thoroughly investigate the needs of the population

f. Understand cohorts of residents who are at risk

g. Conduct Health Needs Assessments

Each Commissioning Support Unit is only permitted to link data listed within this agreement. The pseudonymised data is then passed to the relevant CCG.

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

North East London Commissioning Support Unit also receive identifiable GP data for a GP Practices within the CCGs area. The GP data is received and process as per points i-iv below.

i. Identifiable GP data is extracted from consented GP practices Principal Clinical System via NEL-hosted IM1 GP Extraction service.

ii. Extracted data lands on secure North and East London Commissioning Support Unit GP Environment where strict access is limited to individuals who have been authorised by North and East London DSCRO Business Lead or Senior Information Risk Owner and act on behalf of the Data Controller (GP Practice).

iii. The North and East London Commissioning Support Unit Pseudonym is then applied to GP data within Secure GP Data Environment via a Black Box function. The pseudonymisation enables the linkage with other data sets specified in this DSA.

iv. The agreed specification of Pseudonymised GP data is then made available to CCGs via a secure means of transfer from the secure North and East London Commissioning Support Unit GP environment to the destination CCG or Commissioning Support Unit environment where only pseudonymised data resides.

Optum Health Solutions (UK) Limited

1. NHS Bedfordshire CCG, NHS Luton CCG and NHS Milton Keynes CCG securely pass pseudonymised SUS, Community Services Data Set (CSDS), Mental Health Services Data Set, Local Provider data and GP Primary Care data only to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national data sets and sent as individual data flows.

2. Optum Health Solutions (UK) Ltd provide analysis to:

a. Whole population segmentation to assess population health needs

b. Prospective risk scoring for individuals at risk and an understanding of the drivers of the risk

c. Predictive modelling to determine individuals at risk and an understanding of the drivers of the risk

d. Longitudinal analysis of intersegmental drift - identifying individuals who move between complexity classifications and the drivers of these transitions

e. The production of individual level theographs to identify gaps in care.

3. Allowed linkage is between the datasets contained within point (1) above. GP data, CSDS and Mental Health Services datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity.

4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG.

5. Aggregated required data for CCG Management use will be completed by Optum Health Solutions (UK) Ltd or to 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 with 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 dataset.

7. Optum Health Solutions (UK) Ltd will only be in receipt of data and only be permitted to act as Data Processors for the period specified in the contract with the CCGs. This will be for a period of 20 weeks commencing 30 March 2020.

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:

a. Patients at highest risk of admission

b. Use of high cost activity

c. Frail and elderly

d. Patients that are currently in hospital

e. Patients with most referrals to secondary care

f. Patients with most emergency activity

g. Patients with most expensive prescriptions

h. Patients recently moving from one care setting to another

i. Discharged from hospital

ii. Discharged from community

13. 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

14. 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

15. 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

16. Care co-ordination and planning

a. Planning packages of care

b. Service planning

c. Planning care co-ordination

17. 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 New Models of Care

i. Identifying duplications in care

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

k. Analysing individual and aggregated timelines

18. 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

19. 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

20. 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

21. Comparing expected levels

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

22. 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

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

a. Contract monitoring

b. Contract reconciliation and challenge

c. Invoice validation

24. 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

25. Improving provider data quality

a. Coding audit

b. Data quality validation and review

c. Checking validity of patient identity and commissioner assignment.

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

27. 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.

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

29. Understanding where patients 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.

30. Removal of patients from Risk Stratification reports.

31. 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

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. 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

15. Ensuring compliance with evidence and guidance

a. Testing approaches with evidence and compliance with guidance.

16. Monitoring outcomes

a. Analysis of variation in outcomes across population group

17. 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

18. 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

19. 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

20. 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

21. 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

22. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.

23. 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.

24. Provision of indicators of health problems, and patterns of risk within the commissioning region.

25. Support of benchmarking for evaluating progress in future years.

Not stated in the register.