DSfC - NHS Milton Keynes CCG - 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 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)

- 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

 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

 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 Optum Health Solutions Limited

NHS Milton Keynes CCG is working collaboratively with hospital, community, mental health, ambulance, social care and General Practice health and care providers. Optum Health Solutions Limited will undertake an analytics project which will provide a foundation for integration work across the health and care system. It will introduce patient centric population health insight into the Milton Keynes health and care system. The Bedfordshire, Luton and Milton Keynes STP has signalled its intention to move towards an integrated care system and is an NHS England accelerator site. The population health analytics will provide a foundation for integration work across the system, however at this point is only within Milton Keynes.

Analysis of the linked datasets will present a joined up and comprehensive view of how patient cohorts interact with services across the Milton Keynes health and care system. It will be used to identify and understand priority population segments which clinical and system leaders will design future new care models around. This analytical process will engage leaders, clinicians and managers with how patients accessing their part of the system interact with other providers and services and will provide new insight into care model design. Commissioners and providers will use this insight to identify both short and long-term savings opportunities by identifying unwarranted variation in outcomes and service utilisation between population segments. The analysis outputs will be aggregate with small number suppression applied in line with NHS Digital standards.

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 Milton Keynes CCG (including historical activity where the patient was previously registered or resident in another commissioner).

and/or

• Patients treated by a provider where Milton Keynes 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 Milton Keynes CCG - this is only for commissioning and relates to both national and local flows.

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)

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

Data quality management and pseudonymisation is completed within the DSCRO. Pseudonymisation is undertaken using the Medeanalytics pseudonymisation at source tool. The DSCRO will generate a salt encryption key to be used for this project and will share it with Milton Keynes Council and Apollo Medical (who will be acting as a Data Processor for the GPs) Data is then disseminated as follows:

Data Processor – Optum Health Solutions Limited

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), Diagnostic Imaging data (DIDS) and National Cancer Waiting Times Monitoring Data Set (CWT) only is securely transferred from the DSCRO to Optum Health Solutions Limited.

2. Optum Health Solutions Limited Solutions will receive pseudonymised primary care data from the Milton Keynes General Practices, via their data processor Apollo, using secure FTP. The data is pseudonymised before leaving the GP system.

3. Milton Keynes Council pseudonymise Social Care data using the MedeAnalytics pseudonymisation at source tool. Milton Keynes Council then send pseudonymised Social Care data to Optum Health Solutions Limited

4. Optum Health Solutions Limited add derived fields, link data and provide analysis to:

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

b. Undertake population health management

c. Undertake data quality and validation checks

d. Thoroughly investigate the needs of the population

e. Understand cohorts of residents who are at risk

f. Conduct Health Needs Assessments

5. Allowed linkage is between the data sets contained within points 1, 2 and 3.

6. Aggregation of required data for CCG management use will be completed by Optum Health Solutions Limited or the CCG as instructed by the CCG.

7. Aggregated reports with small number suppression will be sent to the CCG.

8. 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.

No data is sent to, processed or stored by MedeAnalytics.

Optum Health Solutions Limited will not reidentify any data.

Commissioning

1. Linked data quality report – this report will be used to work with data specialists within Milton Keynes to validate the data used against a local view, this will ensure the data is accurate and representative.

2. Initial analytical review of the data for feedback from MK analytics specialists – this report will be used to test and validate insights from Optums analysis with local NHS analytical experts.

3. Initial analytical review of the data for clinical engagement and feedback – this report will be used to validate whether variation in service utilisation between different groups of patients is considered normal by clinicians.

4. Final analytical review for analytical and clinical stakeholders – this report will summarise the key findings from the initial analytical reviews. It also will include analysis on any additional lines of enquiry based on feedback from the initial analytical reviews.

5. Final report for Milton Keynes CCG, Local Authority and GP practices – this report will present the findings of the project to stakeholders across the system. It will include all the key insights and in some cases may include recommendations for new clinical models or advice on population health management strategies, these will be aligned to priority population groups and designed to address unwarranted variation in health outcomes.

Notes on Outputs

• The five reports will only contain aggregate data with small number suppression.

• No record level, patient level or event level data will be shared outside of Optums secure environment.

• All data handled by Optum will be pseudonymised at all times and Optum will not have access to the decryption key.

• Any additional reporting requested by the CCG will be prepared in either an anonymised or aggregate format and will not be shared outside of the CCG unless it is aggregate with small number suppression.

Commissioning

1. Insight into the health needs of the population and how they are changing – the population health analytics will analyse how changes in the population are diving growth in service utilisation across the system.

2. Insight into how well services are aligned to the health needs of the population – the analytics will consider current service delivery and whether it Is optimised for effective population health management.

3. Insight into unwarranted variation in clinical and economic outcomes between population segments (opportunity identification) – the analytics will highlight high levels of variation in cost and utilisation between population groups, these will be clinically validated and fed back into the planning system as potential savings opportunities.

4. Supporting the development of population health management.

5. Supporting the development of integrated care.

Commissioning

1. Insights delivered to MK CCG on population needs, including locality specific information and benchmarking versus regional rates. Specific growth drivers within the population identified and quantified, and insights into high-cost segments of the population delivered.

2. Local providers engaged in conversations around high-cost segments, including how local services are shaped to deliver to these segments. Multiple on-site workshops held with local clinicians and provider management, and insights delivered on specific local needs.

3. Significant clinical engagement in analytics outcomes and further avenues of enquiry explored, and change in clinical behaviour in response to insights has been noted. Further analytical work is required to embed these approaches systematically.

4. Significant capability coaching of local leaders, analysts and clinicians has been undertaken off the back of the work done with this data, and local knowledge of pop health management has increased. Further analytical work is required to embed these approaches systematically.

5. As part of local provider and local authority engagement, integrated care has been the cornerstone of the analytics done to date, and the insights delivered have enabled discussions from across health and social care.