DSfC London Borough of Tower Hamlets Vanguard - Comm

The purpose of the whole systems data-set project is to ensure that resources follow resident’s needs and that the most vulnerable people in Tower Hamlets have their needs met. By analysing routine operational information across the local partner organisations, London Borough of Tower Hamlets Council can better understand the local population’s needs based on the local and residential environment.

This project aims to use routine health, social care and local authority information in a pseudonymised form to better understand the inequalities in health and service use within local communities. This will be used to inform local commissioning, so that we provide the right service in the right place for the right people. The project is led by the London Borough of Tower Hamlets in close collaboration with other THT partners. The work is also overseen by The Institute of Health Equity at University College London.

London Borough of Tower Hamlets have previously received identifiable SUS, Mental Health and Local Provider. This data has been summarised, linked at a patient-level and was then further linked to council and primary care datasets. This culminated in the development of an integrated pseudonymised data-set for the Tower Hamlets Together (THT) Vanguard partnership - this dataset which covers health, social care and the local authority providers. All identifiable data - including personal identifiers such as names, full address and/or postcode and date of birth - has now been destroyed.

The integrated pseudonymised data-set will be used to produce a one-off report aggregated to the level of local Lower Super Output Areas as directed by the Confidentiality Advisory Group (CAG). The database is a means to this end. Identifiable data was only kept for 3 months for linkage and pseudonymisation. The identifiable data has now been destroyed but the integrated pseudonymised data will be kept for 9 months for analysis and to produce the report. It is then kept for a further 12 months for validation of any queries raised on the report. The pseudonymised data will then be destroyed.

THT Vanguard consists of a partnership of providers and commissioners across the local health and care economy.

The THT partnership consists of the:

- Tower Hamlets GP Care Group representing primary care through the collective voice of 36 general practices and their 8 geographic networks,

- Tower Hamlets Clinical Commission Group (CCG)

- Bart’s Health NHS Trust providing acute and community services including accident and emergency services

- East London Foundation Trust providing mental health services

- LBTH providing social care and wider local authority services.

- Tower Hamlets Council for Voluntary Service (THCVS) providing a range of support to residents

Only a summary report will leave the AIMES data haven. Vanguard partners will only receive a finalised aggregate report with small number suppression.

The objectives are:

1. To establish a truly integrated and pseudonymised health, social care and wider determinants of health dataset for the local population which combines information from both the London Borough of Tower Hamlets and the NHS.

a) To clearly describe the health and care provided to a risk stratified Tower Hamlets population with sufficient granularity

b) To define and inform

budgeting for the Tower Hamlet population

2. To achieve 1(a) by quantitatively investigating the association between:

a) the socio-demographic determinants,

b) health status and

c) service usage

to enable sufficiently granular identification of health inequalities in the Borough

3. To explain the variation in spend within the proposed budget in Tower Hamlets

4. To inform local strategic development of new models of care

5. The project will include a robust Patient and Public Involvement (PPI) Plan to work with resident and patient groups to scope and test proposals.

6. The project will also develop informatics capability within the local partnership of providers.

The local authority does not hold a unique identifier in local systems. Only pseudonymised data will be analysed. Pseudonymisation included the removal of data items such as names and addresses but also the reduction of date of births to age in years and post codes to Lower Super Output Areas. Please refer to WSDP Data Set specification for full details of pseudonymisation approach for each items of data.

Now that data is pseudonymised, and held in Zone 2, it will first be descriptively analysed in relation to activity and morbidity levels but subsequent regression analysis will be undertaken in order to understand the relationship between the wider determinants of health and health care activity levels. This will be used to better understand whole systems models to support population need based commissioning.

Data referenced is referenced as pseudonymised although locally after public consultation the London Borough of Tower Hamlets refers to pseudonymised data as depersonalised data.

Commissioning

The data (containing both clinical and financial information) is analysed so that health care provision can be targeted to support the needs of the population within the Local Authority area.

Commissioners commission services from a range of local 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 across a Tower Hamlets Providers partnership.

- Secondary Uses Service (SUS)

- Local Provider Flows

o Acute

o Ambulance

o Community

o Mental Health

- Mental Health Minimum Data Set (MHMDS)

- Mental Health Learning Disability Data Set (MHLDDS)

- Mental Health Services Data Set (MHSDS)

- Children and Young Peoples Service (CYPHS)

- Improving Access to Psychological Therapies (IAPT)

These datasets have been received and destroyed leaving only pseudonymised data. No more identifiable data will be required, and only the pseudonymised will be used going forward. All identifiable data that was held has been destroyed.

The pseudonymised data is required for the following purposes centred on health care commissioning:

- Population health management:

- Targeting care more effectively

- Using value as the redesign principle

- Evidences services to be equitable, effective and efficient

- Assess the impact of the wider determinants of health on health care activity and health

- Better understand the health service needs of the resident population.

- 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

- Modelling and mapping activity across Tower Hamlets

- Support service redesign

- Health Needs Assessment – identification of underlying disease prevalence within the local population and the services populations needs

- Patient stratification and predictive modelling - to identify specific patients at risk of requiring hospital admission and other avoidable factors such as risk of falls and social isolation,

The pseudonymised data is required to ensure that analysis of health care provision the needs of local populations within Tower Hamlets area based on the comprehensive analysis of local health, care and local authority activity.

Processing for commissioning will be conducted by:

- Data Processor 1: North East London Commissioning Support Unit

- Data Processor 2: Queen Mary University of London hosting the Clinical Effectiveness Group

Data Processor 1 – North East London Commissioning Support Unit land the data only. No processing or analysis occurs. The data is required to flow through North East London Commissioning Support Unit in transit only due to the North East London DSCRO firewall only allowing data to flow outwards initially to North East London Commissioning Support Unit. North East London Commissioning Support Units involvement is purely to forward this data received from North East London DSCRO.

Data Processor 2 – Clinical Effectiveness Group within Queen Mary University of London

Queen Mary University of London (QMUL) host the Clinical Effectiveness Group (CEG). The CEG within QMUL is the data processor for the Tower Hamlets Together Whole Systems Data Project (WSDP).

AIMES will hold and store the data only on behalf of the Clinical Effectiveness Group within Queen Mary University of London under instruction of London Borough Tower Hamlets. AIMES are contracted by the Clinical Effectiveness Group within Queen Mary University of London to store data. They do not analyse the data as a data processor. AIMES staff do not have access to any of the data.

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

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 NHS London Borough of Tower Hamlets CCG (including historical activity where the patient was previously registered or resident in another commissioner).

and/or

• Patients treated by a provider where NHS London Borough of Tower Hamlets 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 NHS London Borough of Tower Hamlets CCG - this is only for commissioning and relates to both national and local flows.

Commissioning

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

1. SUS

2. Local Provider Flows (received directly from providers)

o Acute

o Ambulance

o Community

o Mental Health

3. Mental Health Minimum Data Set (MHMDS)

4. Mental Health Learning Disability Data Set (MHLDDS)

5. Mental Health Services Data Set (MHSDS)

6. Children and Young Peoples Service (CYPHS)

7. Improving Access to Psychological Therapies (IAPT)

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

1. Identifiable SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS) data, Children and Young People Services (CYPHS) and Improving Access to Psychological Therapies (IAPT) only was securely transferred from the DSCRO to North East London Commissioning Support Unit.

2. North East London Commissioning Support Unit landed the SUS, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS) Children and Young People Services (CYPHS) and Improving Access to Psychological Therapies (IAPT) data only. No processing or analysis occurs.

3. North East London Commissioning Support Unit then passed the identifiable data to a ring-fenced area within the Clinical Effectiveness Group in Queen Mary University of London – Zone 1.

4. GPs sent identifiable primary care data directly to a ring-fenced area within the Clinical Effectiveness Group in Queen Mary University of London – Zone 1.

5. NHAIS data was sent directly to a ring-fenced area within the Clinical Effectiveness Group in Queen Mary University of London – Zone 1 - from NHS Digital.

6. London Borough of Tower Hamlets sent the Local Authority Minimum Data Set (LAMDS), consisting of identifiable: social care data; enrvironment data; housing data; education data; and library data; to a ring-fenced area within the Clinical Effectiveness Group in Queen Mary University of London – Zone 1.

7. Two members of staff only from the London Borough of Tower Hamlets had access to the data located within Zone 1 in the Clinical Effectiveness Group in Queen Mary University of London. Linkage and pseudonymisation of the data was completed within a three month period following on from access to all health datasets (those described in points in 3, 4, 5, and 6) . The pseudonymised data was then passed into a separate secure area within the Clinical Effectiveness Group in Queen Mary University of London – Zone 2. Once this was complete, all data in Zone 1 was destroyed.

8. The pseudonymised data (in Zone 2) will be analysed in the Clinical Effectiveness Group in Queen Mary University of London to:

o Support the development of new care models through better understanding of the impact of the wider determinants of health on health and care activity to support needs based commissioning of services.

9. Allowed linkage between the data sets contained within point 1, 4, 5 and 6.

10. London Borough Tower Hamlets now have access to the pseudonymised data for to analyse and generate summary analytics

11. The Clinical Effectiveness Group in Queen Mary University of London will provide an aggregate report (after internal governance of IG) with small number suppression to the WSDP governance bodies for review. The WSDP Governance bodies include the WSDP Steering Group and THT Board in addition to the Partnership Joint Information Governance Group.

12. Aggregation of required data will be completed by the Clinical Effectiveness Group in Queen Mary University of London

13. Patient level data will not be shared outside of the Clinical Effectiveness Group in Queen Mary University of London) and will only be shared within the Clinical Effectiveness Group in Queen Mary University of London on a need to know basis (to the selected analysts), as stipulated within the WSDP Project design.

14. The final external publication with small number suppression after approval by the project Board will be available to be shared across provider partners and under Freedom of Information Requests.

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.

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.

Not stated in the register.