DSfC Template 22

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)

- Civil Registries Data (CRD) (Births)

- Civil Registries Data (CRD) (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)

- Adult Social Care Data

Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019.

The pseudonymised data is required to for the following purposes:

 Population health management:

• Understanding the interdependency of care services

• Targeting care more effectively

 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 cohorts of 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

 Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.

 Support measuring the health, mortality or care needs of the total local population.

 Provide intelligence about the safety and effectiveness of medicines.

 Allow analysis of patient pathways across healthcare and social care.

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 NHS Midlands and Lancashire Commissioning Support Unit & Meridian Productivity Limited.

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.

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

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.

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