NHS Digital Data Release Register - reformatted
NHS Wiltshire Ccg projects
272 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
🚩 NHS Wiltshire Ccg was sent multiple files from the same dataset, in the same month, both with optouts respected and with optouts ignored. NHS Wiltshire 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 Wiltshire - RS & IV — DARS-NIC-116560-R7F9J
Type of data: information not disclosed for TRE projects
Opt outs honoured: N, Y, No - data flow is not identifiable, Yes - patient objections upheld, Identifiable (Does not include the flow of confidential data, Section 251, Section 251 NHS Act 2006)
Legal basis: Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Section 251 approval is in place for the flow of identifiable data, 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 2019-07-04 — 2022-07-03 2018.06 — 2020.03.
Access method: Frequent adhoc flow, Frequent Adhoc Flow
Data-controller type: NHS BATH AND NORTH EAST SOMERSET, SWINDON AND WILTSHIRE CCG, NHS BATH AND NORTH EAST SOMERSET, SWINDON AND WILTSHIRE ICB - 92G
Sublicensing allowed: No
Datasets:
- Acute-Local Provider Flows
- Ambulance-Local Provider Flows
- Children and Young People Health
- 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
- Mental Health-Local Provider Flows
- 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
Objectives:
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 South, Central and West CSU
The CCG are advised by South, Central and West CSU whether payment for invoices can be made or not.
Risk Stratification
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.
The legal basis for this to occur is under Section 251 of NHS Act 2006 (CAG 7-04(a)).
Risk Stratification will be conducted by South, Central and West CSU
Commissioning
To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.
The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS+)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
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
§ 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 South, Central and West CSU
Yielded Benefits:
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 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.
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.
Reviewing current service provision
• Cost-benefit analysis and service impact assessments to underpin service transformation across health economy
• Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.)
• Impact analysis for different models or productivity measures, efficiency and experience
• Service and pathway review
• Service utilisation review
Ensuring compliance with evidence and guidance
• Testing approaches with evidence and compliance with guidance.
Monitoring outcomes
• Analysis of variation in outcomes across population groups
Understanding how services impact across the health economy
• Service evaluation
• Programme reviews
• Analysis of productivity, outcomes, experience, plan, targets and actuals
• Assessing value for money and efficiency gains
• Understanding impact of services on health inequalities
Understanding how services impact on the health of the population and patient cohorts
• Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this
• Propensity matching and scoring
• Triple aim analysis
Understanding future drivers for change across health economy
• Forecasting health and care needs for population and population cohorts across STPs
• Identifying changes in disease trends and prevalence
• Efficiencies that can be gained from procuring services across wider footprints, from new innovations
• Predictive modelling
Delivering services that meet changing needs of population
• Analysis to support policy development
• Ethical and equality impact assessments
• Implementation of NMOC
• What do next years contracts need to include?
• Workforce planning
Maximising services and outcomes within financial envelopes across health economy
• What-if analysis
• Cost-benefit analysis
• Health economics analysis
• Scenario planning and modelling
• Investment and disinvestment in services analysis
• Opportunity analysis
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.
1. Output from the risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.
2. Record level output will be available for commissioners (of the CCG), pseudonymised at patient level.
3. 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.
4. 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.
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:
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
Profiling population health and wider determinants to identify and target those most in need
• Understanding population profile and demographics
• Identify patient cohorts with specific needs or who may benefit from interventions
• Identifying disease prevalence. health and care needs for population cohorts
• Contributing to Joint Strategic Needs Assessment (JSNA)
• Geographical mapping and analysis
Identifying and managing preventable and existing conditions
• Identifying types of individuals and population cohorts at risk of non-elective re-admission
• Risk stratification to identify populations suitable for case management
• Risk profiling and predictive modelling
• Risk stratification for planning services for population cohorts
• Identification of disease incidence and diagnosis stratification
Reducing health inequalities
• Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs.
• Socio-demographic analysis
Managing demand
• Waiting times analysis
• Service demand and supply modelling
• Understanding cross-border and overseas visitors
• Winter planning
• Emergency preparedness, business continuity, recovery and contingency planning
Care co-ordination and planning
• Planning packages of care
• Service planning
• Planning care co-ordination
Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
• Patient pathway analysis across health and care
• Outcomes & experience analysis
• Analysis to support anti-terror initiatives
• Analysis to identify vulnerable patients with potential safeguarding issues
• Understanding equity of care and unwarranted variation
• Modelling patient flows
• Tracking patient pathways
• Monitoring to support New Models of Care, Accountable Care Organisations, Sustainable Transformation Plans
• Identifying duplications in care
• Identifying gaps in care, missed diagnoses and triple fail events
• Analysing individual and aggregated timelines
Undertaking budget planning, management and reporting
• Tracking financial performance against plans
• Budget reporting
• Tariff development
• Developing and monitoring capitated budgets
• Developing and monitoring individual-level budgets
• Future budget planning and forecasting
• Paying for care of overseas visitors and cross-border flows
Monitoring the value for money
• Service-level costing & comparisons
• Identification of cost pressures
• Cost benefit analysis
• Equity of spend across services and population cohorts
• Finance impact assessment
Comparing population groups, peers, national and international best practice
• Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
• Benchmarking against other parts of the country
• Identifying unwarranted variation
Comparing expected levels
• Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
Comparing local targets & plans
• Monitoring of local variation in productivity, cost, outcomes, quality and experience
• Local performance dashboards by service provider, commissioner, geography, NMOC, STPs
Monitoring activity and cost compliance against contract and agreed plans
• Contract monitoring
• Contract reconciliation and challenge
• Invoice validation
Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
• Performance dashboards
• CQUIN reporting
• Clinical audit
• Patient experience surveys
• Demand, supply, outcome & experience analysis
• Monitoring cross-border flows and overseas visitor activity
Improving provider data quality
• Coding audit
• Data quality validation and review
• Checking validity of patient identity and commissioner assignment
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 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
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 South, Central and West CSU.
3. South, Central and West CSU 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 South, Central and West 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.
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 South, Central and West CSU, who hold the SUS+ data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to South, Central and West CSU.
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 South, Central and West CSU has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.
Commissioning
The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets:
1. SUS+
2. Local Provider Flows (received directly from providers)
a. Acute
b. Ambulance
c. Community
d. Demand for Service
e. Diagnostic Service
f. Emergency Care
g. Experience, Quality and Outcomes
h. Mental Health
i. Other Not Elsewhere Classified
j. Population Data
k. Primary Care Services
l. Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor 1 – South, Central and West CSU
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) and Diagnostic Imaging data (DIDS) only is securely transferred from the DSCRO to South, Central and West CSU.
2. South, Central and West CSU add derived fields, link data and provide analysis to:
a. See patient journeys for pathways or service design, re-design and de-commissioning.
b. Check recorded activity against contracts or invoices and facilitate discussions with providers.
c. Undertake population health management
d. Undertake data quality and validation checks
e. Thoroughly investigate the needs of the population
f. Understand cohorts of residents who are at risk
g. Conduct Health Needs Assessments
3. Allowed linkage is between the data sets contained within point 1.
4. South, Central and West CSU also receive GP Data. It is received as follows:
a) Identifiable GP data is submitted to the CSU.
b) The data lands in a ring fenced area for GP data only.
c) There is a Data Processing Agreement in place between the GP and the CSU. A specific named individual within the CSU acts on behalf on the GP. This person has been issued with a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box This software cannot be interrogated.
d) The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to that GP and to that specific date.
e) Identifiable data will only be processed by substantive employees of the data controller and processors. Before the CSU will receive the data from the ring fenced area, they require confirmation that the identifiable data has been deleted.
f) The CSU are then sent the pseudonymised GP data (into Database 2) with the pseudo algorithm specific to them.
g) Pseudonymised GP data is then linked to pseudonymised SUS data and an algorithm applied, also used for risk stratification. The out puts are then sent to Database 1.
5. South, Central and West CSU also receive a pseudonymised flow of social care data. Social Care data is received as follows:
a) The social care organisation is issued with their own black box solution.
b) The social care organisation requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once and is specific to that date. The DSCRO is not involved in the processing of personal data for the purpose of pseudonymisation of social care data.
c) The social care organisation submit the pseudonymised social care data to the CSU with the pseudo algorithm specific to them
6. Once the pseudonymised GP data and social care data is received, the CSU make a request to the DSCRO.
7. The DSCRO check the dates of the key generation (Point 4d and 5b).
8. The DSCRO then send a mapping table to the CSU.
9. The CSU then overwrite the organisation specific keys with the DSCRO key.
10. The mapping table is then deleted.
11. The Pseudonymised data in point 1 is securely transferred from the DSCRO to South, Central and West CSU.
12. Social care data and the outputs from Database 2 (Point 5c) are then and GP data (4g) is then linked to the data sets listed within point 1.
13. South, Central and West CSU then pass the processed, pseudonymised and linked data to the CCG.
14. Aggregation of required data for CCG management use will be completed by South, Central and West CSU or the CCG as instructed by the CCG.
15. 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.
Project 2 — NIC-116560-R7F9J
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:2018.03 — 2018.05.
Access method: Ongoing
Data-controller type:
Sublicensing allowed:
Datasets:
- 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-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:
Invoice Validation
As an approved Controlled Environment for Finance (CEfF), South, Central and West CSU receives SUS data identifiable at the level of NHS number according to S.251 CAG 7-07(a) and (c)/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 the CSU 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) (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 General Practitioners (GPs) to better target intervention in Primary Care.
Risk Stratification will be conducted by South, Central and West CSU
Commissioning
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 CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.
The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:
- Secondary Uses Service (SUS)
- Local Provider Flows
o Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
- Mental Health Minimum Data Set (MHMDS)
- Mental Health Learning Disability Data Set (MHLDDS)
- Mental Health Services Data Set (MHSDS)
- Maternity Services Data Set (MSDS)
- Improving Access to Psychological Therapy (IAPT)
- Child and Young People Health Service (CYPHS)
- Diagnostic Imaging Data Set (DIDS)
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 South, Central and West CSU
South, Central and West CSU will conduct risk stratification, invoice validation and general commissioning functions an activities including but not limited to:
- Profiling population health and wider determinants to identify and target those most in need
- Identifying and managing preventable and existing conditions
- Reducing health inequalities
- Managing demand
- Care co-ordination and planning
- Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
- Undertaking budget planning, management and reporting
- Monitoring the value for money
- Comparing population groups, peers, national and international best practice
- Comparing expected levels
- Comparing local targets & plans
- Monitoring activity and cost compliance against contract and agreed plans
- Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
- Improving provider data quality
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.
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. 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.
Reviewing current service provision
• Cost-benefit analysis and service impact assessments to underpin service transformation across health economy
• Service planning and re-design (development of NMoC and integrated care pathways, new partnerships, working with new providers etc.)
• Impact analysis for different models or productivity measures, efficiency and experience
• Service and pathway review
• Service utilisation review
Ensuring compliance with evidence and guidance
• Testing approaches with evidence and compliance with guidance.
Monitoring outcomes
• Analysis of variation in outcomes across population groups
Understanding how services impact across the health economy
• Service evaluation
• Programme reviews
• Analysis of productivity, outcomes, experience, plan, targets and actuals
• Assessing value for money and efficiency gains
• Understanding impact of services on health inequalities
Understanding how services impact on the health of the population and patient cohorts
• Measuring and assessing improvement in service provision, patient experience & outcomes and the cost to achieve this
• Propensity matching and scoring
• Triple aim analysis
Understanding future drivers for change across health economy
• Forecasting health and care needs for population and population cohorts across STPs
• Identifying changes in disease trends and prevalence
• Efficiencies that can be gained from procuring services across wider footprints, from new innovations
• Predictive modelling
Delivering services that meet changing needs of population
• Analysis to support policy development
• Ethical and equality impact assessments
• Implementation of NMOC
• What do next years contracts need to include?
• Workforce planning
Maximising services and outcomes within financial envelopes across health economy
• What-if analysis
• Cost-benefit analysis
• Health economics analysis
• Scenario planning and modelling
• Investment and disinvestment in services analysis
• Opportunity analysis
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 (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.
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.
Profiling population health and wider determinants to identify and target those most in need
• Understanding population profile and demographics
• Identify patient cohorts with specific needs or who may benefit from interventions
• Identifying disease prevalence. health and care needs for population cohorts
• Contributing to Joint Strategic Needs Assessment (JSNA)
• Geographical mapping and analysis
Identifying and managing preventable and existing conditions
• Identifying types of individuals and population cohorts at risk of non-elective re-admission
• Risk stratification to identify populations suitable for case management
• Risk profiling and predictive modelling
• Risk stratification for planning services for population cohorts
• Identification of disease incidence and diagnosis stratification
Reducing health inequalities
• Identifying cohorts of patients who have worse health outcomes typically deprived, ethnic groups, homeless, travellers etc. to enable services to proactively target their needs.
• Socio-demographic analysis
Managing demand
• Waiting times analysis
• Service demand and supply modelling
• Understanding cross-border and overseas visitors
• Winter planning
• Emergency preparedness, business continuity, recovery and contingency planning
Care co-ordination and planning
• Planning packages of care
• Service planning
• Planning care co-ordination
Monitoring individual patient health, service utilisation, pathway compliance experience & outcomes across the heath and care system
• Patient pathway analysis across health and care
• Outcomes & experience analysis
• Analysis to support anti-terror initiatives
• Analysis to identify vulnerable patients with potential safeguarding issues
• Understanding equity of care and unwarranted variation
• Modelling patient flows
• Tracking patient pathways
• Monitoring to support New Models of Care, Accountable Care Organisations, Sustainable Transformation Plans
• Identifying duplications in care
• Identifying gaps in care, missed diagnoses and triple fail events
• Analysing individual and aggregated timelines
Undertaking budget planning, management and reporting
• Tracking financial performance against plans
• Budget reporting
• Tariff development
• Developing and monitoring capitated budgets
• Developing and monitoring individual-level budgets
• Future budget planning and forecasting
• Paying for care of overseas visitors and cross-border flows
Monitoring the value for money
• Service-level costing & comparisons
• Identification of cost pressures
• Cost benefit analysis
• Equity of spend across services and population cohorts
• Finance impact assessment
Comparing population groups, peers, national and international best practice
• Identification of variation in productivity, cost, outcomes, quality, experience, compared with peers, national and international & best practice
• Benchmarking against other parts of the country
• Identifying unwarranted variation
Comparing expected levels
• Standardised comparisons for prevalence, activity, cost, quality, experience, outcomes for given populations
Comparing local targets & plans
• Monitoring of local variation in productivity, cost, outcomes, quality and experience
• Local performance dashboards by service provider, commissioner, geography, NMOC, STPs
Monitoring activity and cost compliance against contract and agreed plans
• Contract monitoring
• Contract reconciliation and challenge
• Invoice validation
Monitoring provider quality, demand, experience and outcomes against contract and agreed plans
• Performance dashboards
• CQUIN reporting
• Clinical audit
• Patient experience surveys
• Demand, supply, outcome & experience analysis
• Monitoring cross-border flows and overseas visitor activity
Improving provider data quality
• Coding audit
• Data quality validation and review
• Checking validity of patient identity and commissioner assignment
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. Access is limited to those substantive employees with authorised user accounts used for identification and authentication.
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.
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.
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 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.
Invoice Validation
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 the South, Central and West CSU.
3. The CSU 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 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 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 South Central, and West CSU 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.
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 South, Central and West CSU, who hold the SUS data within the secure Data Centre on N3.
3. Identifiable GP Data is securely sent from the GP system to South, Central and West CSU.
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. Access to the Risk Stratification system that South, Central and West CSU hosts is limited to those substantive employees with authorised user accounts used for identification and authentication.
7. Once South, Central and West CSU has completed the processing, the CCG can access the online system via a secure N3 connection to access the data pseudonymised at patient level.
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 Acute
o Ambulance
o Community
o Demand for Service
o Diagnostic Service
o Emergency Care
o Experience, Quality and Outcomes
o Mental Health
o Other Not Elsewhere Classified
o Population Data
o Primary Care Services
o Public Health Screening
3. Mental Health Minimum Data Set (MHMDS)
4. Mental Health Learning Disability Data Set (MHLDDS)
5. Mental Health Services Data Set (MHSDS)
6. Maternity Services Data Set (MSDS)
7. Improving Access to Psychological Therapy (IAPT)
8. Child and Young People Health Service (CYPHS)
9. Diagnostic Imaging Data Set (DIDS)
Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows:
Data Processor – South, Central and West CSU
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) and Diagnostic Imaging data (DIDS) only is held within the DSCRO until the completion of points 2 – 8.
2) South, Central and West CSU also receive GP Data. It is received as follows:
a) Identifiable GP data is submitted to the CSU.
b) The data lands in a ring fenced area for GP data only.
c) There is a Data Processing Agreement in place between the GP and the CSU. A specific named individual within the CSU acts on behalf on the GP. This person has been issued with a black box. A black box is a piece of software that processes data by having an input and output that is changed inside the black box This software cannot be interrogated.
d) The individual requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once. The key is specific to that GP and to that specific date.
e) Identifiable data will only be processed by substantive employees of the data controller and processors. Before the CSU will receive the data from the ring fenced area, they require confirmation that the identifiable data has been deleted.
f) The CSU are then sent the pseudonymised GP data (into Database 2) with the pseudo algorithm specific to them.
g) Pseudonymised GP data is then linked to pseudonymised SUS data and an algorithm applied, also used for risk stratification. The out puts are then sent to Database 1.
3) South, Central and West CSU also receive a pseudonymised flow of social care data. Social Care data is received as follows:
a) The social care organisation is issued with their own black box solution.
b) The social care organisation requests a pseudonymisation key from the DSCRO to the black box. The key can only be used once and is specific to that date. The DSCRO is not involved in the processing of personal data for the purpose of pseudonymisation of social care data.
c) The social care organisation submit the pseudonymised social care data to the CSU with the pseudo algorithm specific to them
4) Once the pseudonymised GP data and social care data is received, the CSU make a request to the DSCRO.
5) The DSCRO check the dates of the key generation (Point 2d and 3b).
6) The DSCRO then send a mapping table to the CSU.
7) The CSU then overwrite the organisation specific keys with the DSCRO key.
8) The mapping table is then deleted.
9) The Pseudonymised data in point 1 is securely transferred from the DSCRO to South, Central and West CSU.
10) Social care data and the outputs from Database 2 (Point 2G) are then and GP data is then linked to the data sets listed within point 1.
11) Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG.
12) Patient level data will not be shared outside of the CCG 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
Project 3 — NIC-49745-X5P6X
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 - Mental Health
- Local Provider Data - Other not elsewhere classified
- Local Provider Data - Population Data
- 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
- Maternity Services Dataset
- 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, Other not elsewhere classified, Population Data, Primary Care
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 (c)/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 the CSU 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 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.
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 and will only be used for the purposes laid out in the application/agreement. The data to be released from the HSCIC 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 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
j. 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.
j. 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 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.
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.
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.
Processing:
Central Southern DSCRO will apply Type 2 objections (from 14th October 2016 onwards) before any identifiable data leaves the DSCRO.
Invoice Validation
1. SUS Data is obtained from the SUS Repository to Central Southern Data Services for Commissioners Regional Office (DSCRO).
2. Central Southern DSCRO pushes a one-way data flow of SUS data into the Controlled Environment for Finance (CEfF) in the South Central and West CSU.
3. The CSU 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.
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 the CSU 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.
Risk Stratification
1. SUS Data is sent from the SUS Repository to Central Southern Data Services for Commissioners Regional Office (DSCRO) to the data processor.
2. SUS data identifiable at the level of NHS number regarding hospital admissions, A&E attendances and outpatient attendances is delivered securely from Central Southern DSCRO to the data processor.
3. Data quality management and standardisation of data is completed by Central Southern DSCRO and the data identifiable at the level of NHS number is transferred securely to South Central and West CSU, who hold the SUS data within the secure Data Centre on N3.
4. Identifiable GP Data is securely sent from the GP system to South Central and West CSU.
5. SUS data is linked to GP data in the risk stratification tool by the data processor.
6. 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.
7. South Central and West CSU 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.
8. Once South Central and West CSU 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. Central Southern Data Services for Commissioners Regional Office (DSCRO) obtains a flow of SUS identifiable data for the CCG from the SUS Repository. Central Southern DSCRO also obtains 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 South Central and West CSU for the addition of derived fields, linkage of data sets and analysis. Allowed linkage is between SUS data sets and local flows
3. South Central and West CSU then pass the processed, pseudonymised and linked data to the CCG. The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.
4. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG.
5. 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 where contractual arrangements are in place.
Pseudonymised – Mental Health, MSDS, IAPT, CYPHS and DIDS
1. Central Southern Data Services for Commissioners Regional Office (DSCRO) obtains 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 Central Southern DSCRO and the pseudonymised data is then passed securely to South Central and West CSU for the addition of derived fields and analysis.
3. South Central and West CSU then pass the processed, pseudonymised data to the CCG.
4. The CCG analyses the data to see patient journeys for pathway or service design, re-design and de-commissioning
5. Aggregation of required data for CCG management use will be completed by the CSU or the CCG as instructed by the CCG
6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared where contractual arrangements are in place.