NHS Digital Data Release Register - reformatted

NHS Medway Ccg projects

DSfC - NHS Medway CCG - RS
DSfC - NHS Medway CCG; Comm.
Project 3
Project 4
Project 5
Project 6
Project 7
Project 8

484 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

🚩 NHS Medway Ccg was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Medway Ccg may not have compared the two files, but the identifiers are consistent between datasets, and outside of a good TRE NHS Digital can not know what recipients actually do.

DSfC - NHS Medway CCG - RS — DARS-NIC-226603-C7K2R

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld, Identifiable (Section 251, Section 251 NHS Act 2006)

Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 s261(7); National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)

Sensitive: Sensitive

When:DSA runs 2019-09-01 — 2022-08-31 2018.10 — 2020.03.

Access method: Frequent Adhoc Flow

Data-controller type: NHS KENT AND MEDWAY CCG, NHS KENT AND MEDWAY ICB - 91Q

Sublicensing allowed: No

Datasets:

SUS for Commissioners

Objectives:

Risk stratification is a tool for identifying and predicting which patients are at high risk or are likely to be at high risk and prioritising the management of their care in order to prevent worse outcomes.
To conduct risk stratification Secondary User Services (SUS+) data, identifiable at the level of NHS number is linked with Primary Care data (from GPs) and an algorithm is applied to produce risk scores. Risk Stratification provides focus for future demands by enabling commissioners to prepare plans for patients. Commissioners can then prepare plans for patients who may require high levels of care. Risk Stratification also enables General Practitioners (GPs) to better target intervention in Primary Care.

Risk Stratification will be conducted by Prescribing Services Limited

Yielded Benefits:

Expected Benefits:

Risk stratification promotes improved case management in primary care and will lead to the following benefits being
realised:
1. 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.
2. Improved quality of services through reduced emergency readmissions, especially avoidable emergency admissions. This is achieved through mapping of frequent users of emergency services thus allowing early
intervention.
3. 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.
4. Supports the commissioner to meets its requirement to reduce premature mortality in line with the CCG Outcome Framework by allowing for more targeted intervention in primary care.
5. Better understanding of local population characteristics through analysis of their health and healthcare outcomes.
All of the above lead to improved patient experience through more effective commissioning of services.

Outputs:

1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level.
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS+ data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to:
o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost
o Plan work for commissioning services and contracts
o Set up capitated budgets
o Identify health determinants of risk of admission to hospital, or other adverse care outcomes.

Processing:

Data must only be used as stipulated within this Data Sharing Agreement.

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

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

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.

All access to data is managed under Roles-Based Access Controls

No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality and that data required by the applicant.

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)

The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.

CCGs should work with general practices within their CCG to help them fulfil data controller responsibilities regarding flow of identifiable data into risk stratification tools.

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 section 3 are listed below. This also includes the purpose on which they would be applied -

For the purpose of Risk Stratification:
• Patients who are normally registered and/or resident within the commissioner (including historical activity where the patient was previously registered or resident in another commissioner

Risk Stratification
1. Identifiable SUS+ data is obtained from the SUS Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by the DSCRO and the data identifiable at the level of NHS number is transferred securely to Prescribing Services Ltd, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Prescribing Services Ltd.
4. SUS+ data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data
processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Prescribing Services Ltd has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.

DSfC - NHS Medway CCG; Comm. — DARS-NIC-155188-V0V7L

Type of data: information not disclosed for TRE projects

Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant (Section 251, Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(2)(b)(ii)

Purposes: No (Clinical Commissioning Group (CCG), Sub ICB Location)

Sensitive: Sensitive

When:DSA runs 2019-01-25 — 2022-01-24 2018.06 — 2020.03.

Access method: Frequent adhoc flow, Frequent Adhoc Flow

Data-controller type: NHS KENT AND MEDWAY CCG, NHS KENT AND MEDWAY ICB - 91Q

Sublicensing allowed: No

Datasets:

Acute-Local Provider Flows
Ambulance-Local Provider Flows
Children and Young People Health
Community Services Data Set
Community-Local Provider Flows
Demand for Service-Local Provider Flows
Diagnostic Imaging Dataset
Diagnostic Services-Local Provider Flows
Emergency Care-Local Provider Flows
Experience, Quality and Outcomes-Local Provider Flows
Improving Access to Psychological Therapies Data Set
Maternity Services Data Set
Mental Health and Learning Disabilities Data Set
Mental Health Minimum Data Set
Mental Health Services Data Set
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Population Data-Local Provider Flows
Primary Care Services-Local Provider Flows
Public Health and Screening Services-Local Provider Flows
SUS for Commissioners
Civil Registration - Births
Civil Registration - Deaths
National Cancer Waiting Times Monitoring DataSet (CWT)
National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
Improving Access to Psychological Therapies Data Set_v1.5
Civil Registrations of Death
Community Services Data Set (CSDS)
Diagnostic Imaging Data Set (DID)
Improving Access to Psychological Therapies (IAPT) v1.5
Mental Health and Learning Disabilities Data Set (MHLDDS)
Mental Health Minimum Data Set (MHMDS)
Mental Health Services Data Set (MHSDS)

Objectives:

This is an application for the following purposes:
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 Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
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)
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 CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by:
- MedeAnalytics and Optum Health Solutions

Yielded Benefits:

The CCG would not been able to meet its statutory obligations without this data. In particular the data has enabled us to check the quality and efficiency of the health services we commission and to plan for the future needs of patients. All of the listed outputs and benefits have been realised and are still applicable for the renewal DSA.

Expected Benefits:

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
All of the above will lead to improved patient experience through more effective commissioning of services and enable us and our providers to direct our finite health and social care (public health) resources more efficiently and effectively.
Users can better understand variation in their system, and make comparisons between populations and organisations in a fair and meaningful way with a greater understanding of what normal is. This will support routine opportunity analyses that they carry out in order to best target resources and best understand which activities have had a genuine benefit, and helped reduce costs to the system.
In addition, the platform provides access to comprehensive supporting information that commissioning organisations such as Clinical Commissioning Groups use to ensure that the services they commission:
• deliver the best outcomes for their patients
• cater for and meet the needs of the population they are responsible for;
• monitor condition prevalence within the population
• identify health inequalities and work with local organisations and agencies to remove them

Outputs:

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. Most expensive patients (top 15%)
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 services to react to terror situations
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
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, STPs
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
Analytics Insights
Reports, charts and dashboards providing insights into:
1. 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
2. Data Quality and Validation measures allowing data quality checks on the submitted data
3. Contract Management and Modelling
4. Health needs assessment and predictive modelling instead, 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
5. Understanding impacts and interdependency of care services

Processing:

Data must only be used as stipulated within this Data Sharing Agreement.

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

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

The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG.

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.
All access to data is managed under Roles-Based Access Controls

No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality of interest of the applicant.
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)
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 audited

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 Ambulance
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
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)

Data Processor 1 – MedeAnalytics
Data quality management and pseudonymisation is completed within the DSCRO using the MedeAnalytics tool specific to the CCG and is then disseminated as follows:
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) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to MedeAnalytics.
2) MedeAnalytics also receives the following pseudonymised data from providers that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
o Community Data
o Mental Health Data
o Social Care Data
o GP Data
o Any Qualified Provider data
3) MedeAnalytics add derived fields, link data and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning
o Check recorded activity against contracts or invoices and facilitate discussions with providers
o Undertake population health management
o Undertake data quality and validation checks
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
4) Allowed linkage is between the data sets contained within point 1 and point 2 only.
5) MedeAnalytics then pass the processed, pseudonymised and linked data to the CCG.
6) Aggregation of required data for CCG management use will be completed by MedeAnalytics or the CCG as instructed by the CCG.
7) 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.
8) MedeAnalytics also pass pseudonymised SUS+ and GP data to Optum Health Solutions.

Data Processor 2 – Optum Health Solutions
9) Optum Health Solutions provide analysis to
o Data integration
o Undertake population health management
10) Aggregation of data is completed by Optum Health Solutions.
11) Patient level data will not be shared outside of Optum Health Solutions and will only be shared within Optum Health Solutions 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.

MedeAnalytics outputs only (Direct Care only)
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management service that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
Only GP Practice users are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify, and can only access data to which they have rights under RBAC (which is CG/SIRO approved – within the CCG)
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.
For clarity: Optum require data for our more transformational Public Health facing tools such as Health Population Manager whereas MedeAnalytics will be dealing with the day to day more transactional (SUS, SLAM, MH, Community…) data feeds required for contracting and commissioning purposes.

Project 3 — DARS-NIC-170585-V9Q4L

Type of data: information not disclosed for TRE projects

Opt outs honoured: Yes - patient objections upheld (Section 251)

Legal basis: Section 251 approval is in place for the flow of identifiable data, National Health Service Act 2006 - s251 - 'Control of patient information'.

Purposes: ()

Sensitive: Sensitive

When:2018.06 — 2019.04.

Access method: Frequent adhoc flow, Frequent Adhoc Flow

Data-controller type:

Sublicensing allowed:

Datasets:

SUS for Commissioners

Objectives:

This is an application for the following purposes:
Invoice Validation
Invoice validation is part of a process by which providers of care or services get paid for the work they do.
Invoices are submitted to the Clinical Commissioning Group (CCG) so they are able to ensure that the activity claimed for each patient is their responsibility. This is done by processing and analysing Secondary User Services (SUS+) data, which is received into a secure Controlled Environment for Finance (CEfF). The SUS+ data is identifiable at the level of NHS number. The NHS number is only used to confirm the accuracy of backing-data sets and will not be used further.
The legal basis for this to occur is under Section 251 of NHS Act 2006.
Invoice Validation with be conducted by:
- Optum Health Solutions
The CCG are advised by the data processor whether payment for invoices can be made or not.

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Processing:

Data must only be used as stipulated within this Data Sharing Agreement.

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

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

The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG.

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.
All access to data is managed under Roles-Based Access Controls

No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality of interest of the applicant.
The DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
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)

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 audited

Data for the purpose of Invoice Validation is kept within the CEfF, and only used by staff properly trained and authorised for the activity. Only CEfF staff are able to access data in the CEfF and only CEfF staff operate the invoice validation process within the CEfF. Data flows directly in to the CEfF from the DSCRO and from the providers – it does not flow through any other processors.

Invoice Validation
Optum Health Solutions
1. Identifiable SUS+ Data is obtained from the SUS+ Repository to the Data Services for Commissioners Regional Office (DSCRO).
2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in Optum Health Solutions.
3. Optum Health Solutions carry out the following processing activities within the CEfF for invoice validation purposes:
a. Validating that the Clinical Commissioning Group is responsible for payment for the care of the individual by using SUS+ and/or backing flow data.
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by NHS Digital to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
4. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between Optum Health Solutions CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc.

Project 4 — DARS-NIC-88562-G4W4K

Type of data: information not disclosed for TRE projects

Opt outs honoured: N (Section 251)

Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii)

Purposes: ()

Sensitive: Sensitive

When:2018.06 — 2018.09.

Access method: Frequent adhoc flow

Data-controller type:

Sublicensing allowed:

Datasets:

Diagnostic Services-Local Provider Flows
Improving Access to Psychological Therapies Data Set
Maternity Services Data Set
Mental Health and Learning Disabilities Data Set

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (b)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by Medway CCG whether payment for invoices can be made or not.

Risk Stratification
To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care.

Pseudonymised – SUS and Local Flows
To use pseudonymised data to provide intelligence to support commissioning of health services. 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.
The CCG commissions 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- 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)
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.

No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed. Data will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Risk Stratification
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. 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.
2. 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.
3. 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.
4. 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.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.

Pseudonymised – SUS and Local Flows
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. 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. 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.

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (at the CCG), pseudonymised at patient level.
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to:
o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost
o Plan work for commissioning services and contracts
o Set up capitated budgets
o Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
Pseudonymised – SUS and Local Flows
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. Data quality reporting and resolution of issues.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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. Data quality reporting and resolution of issues.

Processing:

South London DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.

The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to substantive employees with authorised user accounts used for identification and authentication.

Invoice Validation
1. SUS Data is obtained from the SUS Repository by South London DSCRO.
2. South London DSCRO pushes a one-way data flow of SUS data into the Data Warehouse for Medway CCG, which is held in a secure environment within Maidstone and Tunbridge Wells NHS Trust.
3. Staff within the Controlled Environment for Finance (CEfF) in the Medway CCG access the Data Warehouse via Role Based Access Controls.
4. Medway CCG carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by the HSCIC to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the Medway CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Access to the system is restricted to the Medway CEfF team and access is role based. CCGs only received data relating to their own CCG.

Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository to South London Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by South London DSCRO and the data identifiable at the level of NHS number is transferred securely to Maidstone and Tunbridge Wells NHS Trust who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Maidstone and Tunbridge Wells NHS Trust.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Maidstone and Tunbridge Wells NHS Trust who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once Maidstone and Tunbridge Wells NHS Trust has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.

Pseudonymised – SUS and Local Flows
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of SUS identifiable data for the CCG from the SUS Repository. South London DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of local contract rules and tariffs.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the HES analysis guide can be shared.

Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of derived fields and analysis.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the rules listed in Appendix C of the Data Sharing Agreement as follows:
- Presented National level figures only may be presented unrounded without the small number suppression
- Suppress all numbers between 0 and 4
- Round all other numbers to the nearest 5
- Percentages can be calculated based on unrounded values, but need to be rounded to the nearest integer in any outputs

Project 5 — NIC-88562-G4W4K

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Y

Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2017.12 — 2018.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
SUS for Commissioners
Public Health and Screening Services-Local Provider Flows
Primary Care Services-Local Provider Flows
Mental Health-Local Provider Flows
Mental Health Services Data Set
Mental Health Minimum Data Set
Mental Health and Learning Disabilities Data Set
Maternity Services Data Set
Improving Access to Psychological Therapies Data Set
Experience, Quality and Outcomes-Local Provider Flows
Emergency Care-Local Provider Flows
Diagnostic Services-Local Provider Flows
Diagnostic Imaging Dataset
Demand for Service-Local Provider Flows
Community-Local Provider Flows
Children and Young People Health
Ambulance-Local Provider Flows
Acute-Local Provider Flows

Objectives:

Objective for processing:
This is a new application for the following purposes:
Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (b)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by Medway CCG whether payment for invoices can be made or not.

Risk Stratification
To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care.

Pseudonymised – SUS and Local Flows
To use pseudonymised data to provide intelligence to support commissioning of health services. 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.
The CCG commissions 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- 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)
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.

No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed. Data will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

Expected measurable benefits to health and/or social care including target date:
Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Risk Stratification
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. 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.
2. 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.
3. 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.
4. 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.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.

Pseudonymised – SUS and Local Flows
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. 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. 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.

Outputs:

Specific outputs expected, including target date:
Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (at the CCG), pseudonymised at patient level.
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to:
o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost
o Plan work for commissioning services and contracts
o Set up capitated budgets
o Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
Pseudonymised – SUS and Local Flows
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. Data quality reporting and resolution of issues.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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. Data quality reporting and resolution of issues.

Processing:

Processing activities:
South London DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those administrative staff with authorised user accounts used for identification and authentication.
The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to substantive employees with authorised user accounts used for identification and authentication.

Invoice Validation
1. SUS Data is obtained from the SUS Repository by South London DSCRO.
2. South London DSCRO pushes a one-way data flow of SUS data into the Data Warehouse for Medway CCG, which is held in a secure environment within Maidstone and Tunbridge Wells NHS Trust.
3. Staff within the Controlled Environment for Finance (CEfF) in the Medway CCG access the Data Warehouse via Role Based Access Controls.
4. Medway CCG carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by the HSCIC to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the Medway CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Access to the system is restricted to the Medway CEfF team and access is role based. CCGs only received data relating to their own CCG.

Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository to South London Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by South London DSCRO and the data identifiable at the level of NHS number is transferred securely to Maidstone and Tunbridge Wells NHS Trust who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Maidstone and Tunbridge Wells NHS Trust.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Maidstone and Tunbridge Wells NHS Trust who hosts the risk stratification system that holds SUS data is limited to those administrative staff with authorised user accounts used for identification and authentication.
7. Once Maidstone and Tunbridge Wells NHS Trust has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.

Pseudonymised – SUS and Local Flows
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of SUS identifiable data for the CCG from the SUS Repository. South London DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of local contract rules and tariffs.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the HES analysis guide can be shared.

Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of derived fields and analysis.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the rules listed in Appendix C of the Data Sharing Agreement as follows:
- Presented National level figures only may be presented unrounded without the small number suppression
- Suppress all numbers between 0 and 4
- Round all other numbers to the nearest 5
- Percentages can be calculated based on unrounded values, but need to be rounded to the nearest integer in any outputs

Project 6 — NIC-155188-V0V7L

Type of data: information not disclosed for TRE projects

Opt outs honoured: N

Legal basis: Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2017.12 — 2018.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

SUS data (Accident & Emergency, Admitted Patient Care & Outpatient)
Improving Access to Psychological Therapies Data Set
Mental Health Services Data Set
Local Provider Data - Acute
Local Provider Data - Ambulance
Local Provider Data - Community
Local Provider Data - Demand for Service
Local Provider Data - Diagnostic Services
Local Provider Data - Emergency Care
Local Provider Data - Experience Quality and Outcomes
Local Provider Data - Mental Health
Local Provider Data - Other not elsewhere classified
SUS for Commissioners
Public Health and Screening Services-Local Provider Flows
Primary Care Services-Local Provider Flows
Population Data-Local Provider Flows
Other Not Elsewhere Classified (NEC)-Local Provider Flows
Mental Health Minimum Data Set
Mental Health and Learning Disabilities Data Set
Maternity Services Data Set
Experience, Quality and Outcomes-Local Provider Flows
Emergency Care-Local Provider Flows
Diagnostic Services-Local Provider Flows
Diagnostic Imaging Dataset
Demand for Service-Local Provider Flows
Community-Local Provider Flows
Community Services Data Set
Children and Young People Health
Ambulance-Local Provider Flows
Acute-Local Provider Flows

Objectives:

Objective for processing:
This is an application for the following purposes:
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 Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
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)
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 CCG area based on the full analysis of multiple pseudonymised datasets.
Processing for commissioning will be conducted by:
- MedeAnalytics and Optum Health Solutions

Expected Benefits:

Expected measurable benefits to health and/or social care including target date:
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
All of the above will lead to improved patient experience through more effective commissioning of services and enable us and our providers to direct our finite health and social care (public health) resources more efficiently and effectively.
Users can better understand variation in their system, and make comparisons between populations and organisations in a fair and meaningful way with a greater understanding of what normal is. This will support routine opportunity analyses that they carry out in order to best target resources and best understand which activities have had a genuine benefit, and helped reduce costs to the system.
In addition, the platform provides access to comprehensive supporting information that commissioning organisations such as Clinical Commissioning Groups use to ensure that the services they commission:
• deliver the best outcomes for their patients
• cater for and meet the needs of the population they are responsible for;
• monitor condition prevalence within the population
• identify health inequalities and work with local organisations and agencies to remove them

Outputs:

Specific outputs expected, including target date:
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. Most expensive patients (top 15%)
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 services to react to terror situations
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
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, STPs
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
Analytics Insights
Reports, charts and dashboards providing insights into:
1. 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
2. Data Quality and Validation measures allowing data quality checks on the submitted data
3. Contract Management and Modelling
4. Health needs assessment and predictive modelling instead, 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
5. Understanding impacts and interdependency of care services

Processing:

Processing activities:
Data must only be used as stipulated within this Data Sharing Agreement.

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

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

The Data Controller and any Data Processor will only have access to records of patients of residence and registration within the CCG.

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.
All access to data is managed under Roles-Based Access Controls

No patient level data will be linked other than as specifically detailed within this agreement. Data 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, but only that data relating to the specific locality of interest of the applicant.
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)
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 audited

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 Ambulance
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
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)

Data Processor 1 – MedeAnalytics
Data quality management and pseudonymisation is completed within the DSCRO using the MedeAnalytics tool specific to the CCG and is then disseminated as follows:
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) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to MedeAnalytics.
2) MedeAnalytics also receives the following pseudonymised data from providers that has been pseudonymised at source using the MedeAnalytics pseudonymisation tool:
o Community Data
o Mental Health Data
o Social Care Data
o GP Data
o Any Qualified Provider data
3) MedeAnalytics add derived fields, link data and provide analysis to:
o See patient journeys for pathways or service design, re-design and de-commissioning
o Check recorded activity against contracts or invoices and facilitate discussions with providers
o Undertake population health management
o Undertake data quality and validation checks
o Thoroughly investigate the needs of the population
o Understand cohorts of residents who are at risk
o Conduct Health Needs Assessments
4) Allowed linkage is between the data sets contained within point 1 and point 2 only.
5) MedeAnalytics then pass the processed, pseudonymised and linked data to the CCG.
6) Aggregation of required data for CCG management use will be completed by MedeAnalytics or the CCG as instructed by the CCG.
7) 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.
8) MedeAnalytics also pass pseudonymised SUS+ and GP data to Optum Health Solutions.

Data Processor 2 – Optum Health Solutions
9) Optum Health Solutions provide analysis to
o Data integration
o Undertake population health management
10) Aggregation of data is completed by Optum Health Solutions.
11) Patient level data will not be shared outside of Optum Health Solutions and will only be shared within Optum Health Solutions 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.

MedeAnalytics outputs only (Direct Care only)
Re-identification (managed under RBAC) requires an additional step to access re-identification keys held by an independent third party key management service that has no access to the data. Disabling a user’s account in the key management system immediately removes the ability of that user to access re-identification keys.
Each Re-identification requires a different key, so inappropriate retention of keys (which is neither allowed, nor easy to accomplish by design) will not result in compromise of data
Only GP Practice users are able to re-identify patients and only when they have a legitimate reason and a legal right to re-identify, and can only access data to which they have rights under RBAC (which is CG/SIRO approved – within the CCG)
All data providers for a particular region (according to contract) are issued with encryption keys that ensure data for their region can only be linked to data from other providers for the same region. This means that data for two different regional customers cannot be accidentally mixed.
For clarity: Optum require data for our more transformational Public Health facing tools such as Health Population Manager whereas MedeAnalytics will be dealing with the day to day more transactional (SUS, SLAM, MH, Community…) data feeds required for contracting and commissioning purposes.

Project 7 — NIC-88562-J4W4K

Type of data: information not disclosed for TRE projects

Opt outs honoured: N, Y

Legal basis: Health and Social Care Act 2012, Section 251 approval is in place for the flow of identifiable data

Purposes: ()

Sensitive: Sensitive

When:2017.06 — 2017.05.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

Children and Young People's Health Services Data Set
Improving Access to Psychological Therapies Data Set
Local Provider Data - Acute
Local Provider Data - Ambulance
Local Provider Data - Community
Local Provider Data - Demand for Service
Local Provider Data - Diagnostic Services
Local Provider Data - Emergency Care
Local Provider Data - Experience Quality and Outcomes
Local Provider Data - Public Health & Screening services
Local Provider Data - Mental Health
Local Provider Data - Primary Care
Mental Health and Learning Disabilities Data Set
Mental Health Minimum Data Set
Mental Health Services Data Set
SUS Accident & Emergency data
SUS Admitted Patient Care data
SUS Outpatient data

Objectives:

Objective for processing:
This is a new application for the following purposes:
Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (b)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by Medway CCG whether payment for invoices can be made or not.

Risk Stratification
To use SUS data identifiable at the level of NHS number according to S.251 CAG 7-04(a)/2013 (and Primary Care Data) for the purpose of Risk Stratification. Risk Stratification provides a forecast of future demand by identifying high risk patients. This enables commissioners to initiate proactive management plans for patients that are potentially high service users. Risk Stratification enables GPs to better target intervention in Primary Care.

Pseudonymised – SUS and Local Flows
To use pseudonymised data to provide intelligence to support commissioning of health services. 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.
The CCG commissions 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- 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)
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.

No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed. Data will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Risk Stratification
Risk stratification promotes improved case management in primary care and will lead to the following benefits being realised:
1. 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.
2. 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.
3. 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.
4. 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.
5. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.
All of the above lead to improved patient experience through more effective commissioning of services.

Pseudonymised – SUS and Local Flows
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. 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. 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.

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Risk Stratification
1. As part of the risk stratification processing activity detailed above, GPs have access to the risk stratification tool which highlights patients for whom the GP is responsible and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
2. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
3. Record level output will be available for commissioners (at the CCG), pseudonymised at patient level.
4. GP Practices will be able to view the risk scores for individual patients with the ability to display the underlying SUS data for the individual patients when it is required for direct care purposes by someone who has a legitimate relationship with the patient.
5. The CCG will be able to target specific patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions. The CCG will also be able to:
o Stratify populations based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost
o Plan work for commissioning services and contracts
o Set up capitated budgets
o Identify health determinants of risk of admission to hospital, or other adverse care outcomes.
Pseudonymised – SUS and Local Flows
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. Data quality reporting and resolution of issues.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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. Data quality reporting and resolution of issues.

Processing:

South London DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to substantive employees with authorised user accounts used for identification and authentication.

Invoice Validation
1. SUS Data is obtained from the SUS Repository by South London DSCRO.
2. South London DSCRO pushes a one-way data flow of SUS data into the Data Warehouse for Medway CCG, which is held in a secure environment within Maidstone and Tunbridge Wells NHS Trust.
3. Staff within the Controlled Environment for Finance (CEfF) in the Medway CCG access the Data Warehouse via Role Based Access Controls.
4. Medway CCG carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by the HSCIC to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the Medway CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Access to the system is restricted to the Medway CEfF team and access is role based. CCGs only received data relating to their own CCG.

Risk Stratification
1. Identifiable SUS data is obtained from the SUS Repository to South London Data Services for Commissioners Regional Office (DSCRO).
2. Data quality management and standardisation of data is completed by South London DSCRO and the data identifiable at the level of NHS number is transferred securely to Maidstone and Tunbridge Wells NHS Trust who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to Maidstone and Tunbridge Wells NHS Trust.
4. SUS data is linked to GP data in the risk stratification tool by the data processor.
5. As part of the risk stratification processing activity, GPs have access to the risk stratification tool within the data processor, which highlights patients with whom the GP has a legitimate relationship and have been classed as at risk. The only identifier available to GPs is the NHS numbers of their own patients. Any further identification of the patients will be completed by the GP on their own systems.
6. Once Maidstone and Tunbridge Wells NHS Trust has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.

Pseudonymised – SUS and Local Flows
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of SUS identifiable data for the CCG from the SUS Repository. South London DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of local contract rules and tariffs.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the HES analysis guide can be shared.

Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of derived fields and analysis.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the rules listed in Appendix C of the Data Sharing Agreement as follows:
- Presented National level figures only may be presented unrounded without the small number suppression
- Suppress all numbers between 0 and 4
- Round all other numbers to the nearest 5
- Percentages can be calculated based on unrounded values, but need to be rounded to the nearest integer in any outputs

Project 8 — NIC-43551-Y0W5M

Type of data: information not disclosed for TRE projects

Opt outs honoured: Y, N

Legal basis: Section 251 approval is in place for the flow of identifiable data, Health and Social Care Act 2012

Purposes: ()

Sensitive: Sensitive

When:2016.12 — 2017.02.

Access method: Ongoing

Data-controller type:

Sublicensing allowed:

Datasets:

SUS (Accident & Emergency, Inpatient and Outpatient data)
Local Provider Data - Acute, Ambulance, Community, Demand for Service, Diagnostic Services, Emergency Care, Experience Quality and Outcomes, Mental Health, Primary Care, Public Health & Screening services
Mental Health Minimum Data Set
Mental Health and Learning Disabilities Data Set
Mental Health Services Data Set
Improving Access to Psychological Therapies Data Set
Children and Young People's Health Services Data Set

Objectives:

Invoice Validation
As an approved Controlled Environment for Finance (CEfF), the data processor receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (b)/2013, to undertake invoice validation on behalf of the CCG. NHS number is only used to confirm the accuracy of backing-data sets and will not be shared outside of the CEfF. The CCG are advised by Medway CCG whether payment for invoices can be made or not.

Pseudonymised – SUS and Local Flows
To use pseudonymised data to provide intelligence to support commissioning of health services. 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.
The CCG commissions 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
To use pseudonymised data for the following datasets to provide intelligence to support commissioning of health services :
- 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)
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.

No record level data will be linked other than as specifically detailed within this application/agreement. Data will only be shared with those parties listed. Data will only be used for the purposes laid out in the application/agreement. The data to be released from the NHS Digital will not be national data, but only that data relating to the specific locality of interest of the applicant.

Expected Benefits:

Invoice Validation
1. Financial validation of activity
2. CCG Budget control
3. Commissioning and performance management
4. Meeting commissioning objectives without compromising patient confidentiality
5. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

Pseudonymised – SUS and Local Flows
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. 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.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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.
4. Commissioning cycle support for grouping and re-costing previous activity.
5. Enables monitoring of:
a. CCG outcome indicators.
b. 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.

Outputs:

Invoice Validation
1. Addressing poor data quality issues
2. Production of reports for business intelligence
3. Budget reporting
4. Validation of invoices for non-contracted events

Pseudonymised – SUS and Local Flows
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. Data quality reporting and resolution of issues.

Pseudonymised – Mental Health, Maternity, IAPT, CYPHS and DIDS
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 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. Data quality reporting and resolution of issues.

Processing:

South London DSCRO (part of NHS Digital) will apply Type 2 objections before any identifiable data leaves the DSCRO.
The CCG and any Data Processor will only have access to records of its own CCG. Access is limited to those administrative staff with authorised user accounts used for identification and authentication.
Invoice Validation
1. SUS Data is obtained from the SUS Repository by South London DSCRO.
2. South London DSCRO pushes a one-way data flow of SUS data into the Data Warehouse for Medway CCG, which is held in a secure environment within Maidstone and Tunbridge Wells NHS Trust.
3. Staff within the Controlled Environment for Finance (CEfF) in the Medway CCG access the Data Warehouse via Role Based Access Controls.
4. Medway CCG carry out the following processing activities within the CEfF for invoice validation purposes:
a. Checking the individual is registered to a particular Clinical Commissioning Group (CCG) and associated with an invoice from the national SUS data flow to validate the corresponding record in the backing data flow
b. Once the backing information is received, this will be checked against national NHS and local commissioning policies as well as being checked against system access and reports provided by the HSCIC to confirm the payments are:
i. In line with Payment by Results tariffs
ii. are in relation to a patient registered with a CCG GP or resident within the CCG area.
iii. The health care provided should be paid by the CCG in line with CCG guidance.
5. The CCG are notified that the invoice has been validated and can be paid. Any discrepancies or non-validated invoices are investigated and resolved between the Medway CEfF team and the provider meaning that no identifiable data needs to be sent to the CCG. The CCG only receives notification to pay and management reporting detailing the total quantum of invoices received pending, processed etc. Access to the system is restricted to the Medway CEfF team and access is role based. CCGs only received data relating to their own CCG.

Pseudonymised – SUS and Local Flows
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of SUS identifiable data for the CCG from the SUS Repository. South London DSCRO also receives identifiable local provider data for the CCG directly from Providers.
2. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of local contract rules and tariffs.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the HES analysis guide can be shared.

Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. South London Data Services for Commissioners Regional Office (DSCRO) obtain a flow of data identifiable at the level of NHS number for Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) for commissioning purposes.
2. Data quality management and pseudonymisation of data is completed by South London DSCRO and the pseudonymised data is then passed securely to Maidstone and Tunbridge Wells NHS Trust for the addition of derived fields and analysis.
3. Maidstone and Tunbridge Wells NHS Trust then pass the processed, pseudonymised and linked data to the CCG who analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Dissemination from Maidstone and Tunbridge Wells NHS Trust to the CCG is via a warehoused database that is controlled on a user by user access rights basis. Access is limited to the contract and performance team that operates across the three North Kent CCGs.
5. The data warehouse, via the access rights, allows protected ‘views’ of the tables by the Central Support Team who have role based access in order to write queries on the episode/record level pseudonymised data. Only substantive employees of the Trust have access to the data.
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 in line with the rules listed in Appendix C of the Data Sharing Agreement.