DSfC - NHS Sheffield CCG - COMM, IV, RS

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 the CCG is 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 (data from providers) and will not be used further.

The CCG are advised by the appointed CEfF whether payment for invoices can be made or not.

Invoice Validation with be conducted by Rotherham CCG and Liaison Financial Services.

Liaison Financial Services Ltd conduct an independent ad-hoc review on retrospective payments made. Investing resource, skills and experience into deeper reconciliation, this identifies overcharges already paid and recovers savings for the CCG that would otherwise be lost.

RISK STRATIFICATION

Risk stratification is a tool for identifying and predicting which patients are at high risk (of health deterioration and using multiple services) 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 both individual and groups of vulnerable 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 North of England Commissioning Support Unit (NECS), Methods Analytics and Prescribing Services Limited

Commissioning

To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area.

The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers.

The following pseudonymised datasets are required to provide intelligence to support commissioning of health services:

- Secondary Uses Service (SUS+)

- Local Provider Flows

o Acute

o Ambulance

o Community

o Demand for Service

o Diagnostic Service

o Emergency Care

o Experience, Quality and Outcomes

o Mental Health

o Other Not Elsewhere Classified

o Population Data

o Primary Care Services

o Public Health Screening

- Mental Health Minimum Data Set (MHMDS)

- Mental Health Learning Disability Data Set (MHLDDS)

- Mental Health Services Data Set (MHSDS)

- Maternity Services Data Set (MSDS)

- Improving Access to Psychological Therapy (IAPT)

- Child and Young People Health Service (CYPHS)

- Diagnostic Imaging Data Set (DIDS)

- National Cancer Waiting Times Monitoring Data Set (CWT)

- Civil Registries Data (CRD) (Births)

- Civil Registries Data (CRD) (Deaths)

- National Diabetes Audit (NDA)

- Patient Reported Outcome Measures (PROMs)

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 North of England Commissioning Support Unit (NECS), Methods Analytical Ltd, Sheffield Hallam University, University of Sheffield & Attain Health Management Services Ltd

PROCESSING CONDITIONS:

Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital.

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

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

All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake.

Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement.

NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data)

The DSCRO (part of NHS Digital) will apply National Opt-outs before any identifiable data leaves the DSCRO only for the purpose of Risk Stratification.

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.

(RS) The only identifier available in the data set is the NHS numbers. Any further identification of the patients will only be completed by the patient’s clinician on their own systems for the purpose of direct care with a legitimate relationship.

ONWARD SHARING:

There is no requirement for the analytical teams to re-identify patients, but in the development of cohorts of patients considered to be at risk, the data controllers may need the facility to provide identifiable results back to direct healthcare professionals or local authority direct care staff only for the purpose of direct care. All re-id requests will be processed and authorised by the DSCRO on a case by case basis. National data opt outs are not applied in these cases as they are for the purposes of direct care which follows the legal basis of implied consent.

An example of a request for the re-id of patients for direct care may be;

A&E High Attendance usage

The CCG can filter data to show for example the number of A&E attendances in a given period for each patient. The CCG can then flag to the relevant GP of the patient any patients that require intervention. An outcome of this is earlier intervention in the patient(s) care thus potentially reducing future costs and minimising future risk.

Polypharmacy re-IDs

CCG's can request re-ID of a list of patients to be sent to the relevant GP with a high number of medications (ingredient count) and review the medication for these patients. This can help address the risk of polypharmacy which is recognised as an adverse risk factor for patient safety. A by-product of such reviews may be to reduce costs of medication.

The Re-identification process for direct care is as follows:

1. The CCG identifies a patient cohort (typically small numbers) to be re-identified for the purpose of direct care.

2. The CCG sends a re-id request to the DSCRO. This may be done through the CCG or CSU’s Business Intelligence (BI) Tool, or through a manual form.

3. The DSCRO (either through an automated system or manual checking in line with the request) assesses as to whether the request passes the specified re-identification process checks. Checks include if the requester is authorised to access identifiable data, if the number of patients in the cohort is appropriate, and that the request does not seem inappropriate or outside of expected parameters, including for example around timings and the requestor’s relationship with patients in the data

4. If successful/approved, the DSCRO re-identifies the relevant data item(s) for the appropriate patients and returns the identifiable fields to Health or care professional(s) with a legitimate relationship to the patient. The CCG does not see the identifiable record.

5. DSCROs retain an audit trail of all re-id requests

6. National Data opt outs are not applied for the purpose of direct care

Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set.

SEGREGATION:

Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked.

Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked.

All access to data is auditable by NHS Digital.

Data 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.

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 Commissioning:

• 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).

and/or

• Patients treated by a provider where the commissioner is the host/co-ordinating commissioner and/or has the primary responsibility for the provider services in the local health economy – this is only for commissioning and relates to both national and local flows.

and/or

• Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of the commissioner - this is only for commissioning and relates to both national and local flows.

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

For the purpose of Invoice Validation:

• CCG of residence and/or registration.

The above relates to data requested only (Table 3B). Data currently held (Table 3A) will have the following Data Minimisation:

• CCG of residence and/or registration

Microsoft Limited supply provide Cloud Services for Liaison Financial Services Ltd and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Oracle Corporation UK Ltd provide Cloud Services for NHS Sheffield CCG under the controls of North of England Commissioning Support Unit and are therefore listed as a data processor. They supply support to the system, but do not access data. Therefore, any access to the data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Database Service Provider Global LTD will be providing NHS North of England Commissioning Support Unit with support for the Oracle platform, including database administration support, and are therefore listed as a data processor. Using the data for any other purpose would be considered a breach of this agreement.

For clarity, any access by Nexent, Yeadon Community Health Centre and The Bunker Secure Hosting Ltd to data held under this agreement would be considered a breach of the agreement. This includes granting of access to the database[s] containing the data.

Invoice Validation

Data Processor 6 - Rotherham CCG

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 Rotherham CCG

3. The CEfF also receive backing data from the provider.

4. The CCG 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.

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 Rotherham CCG 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.

INVOICE VALIDATION - Liaison Financial Services Ltd

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 Liaison Financial Services Ltd.

3. The CEfF also receive backing data from the provider.

4. Liaison Financial Services Ltd carry out the following processing activities within the CEfF for invoice validation purposes:

a. Validating that the Clinical Commissioning Group are responsible for payment for the care of the individual by using SUS+ and/or provider backing flow data.

b. Once the provider 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.

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 Liaison Financial Services Ltd 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

Data Processor 1 - North of England Commissioning Support Unit (NECS)

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 North of England Commissioning Support Unit (NECS), who hold the SUS+ data within the secure Data Centre on N3.

3. Identifiable GP Data is securely sent from the GP system to North of England Commissioning Support Unit (NECS)

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 North of England Commissioning Support Unit (NECS) has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.

Data Processor 2 – Methods Analytical Ltd

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 Methods Analytical 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 Methods Analytical 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 Methods Analytical Ltd has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level.

Data Processor 7 - Prescribing Services Ltd

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.

Commissioning

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

1. SUS+

2. Local Provider Flows (received directly from providers)

a. Acute

b. Ambulance

c. Community

d. Demand for Service

e. Diagnostic Service

f. Emergency Care

g. Experience, Quality and Outcomes

h. Mental Health

i. Other Not Elsewhere Classified

j. Population Data

k. Primary Care Services

l. Public Health Screening

3. Mental Health Minimum Data Set (MHMDS)

4. Mental Health Learning Disability Data Set (MHLDDS)

5. Mental Health Services Data Set (MHSDS)

6. Maternity Services Data Set (MSDS)

7. Improving Access to Psychological Therapy (IAPT)

8. Child and Young People Health Service (CYPHS)

9. Diagnostic Imaging Data Set (DIDS)

10. Community Services Data Set (CSDS)

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

12. Civil Registries Data (CRD) (Births)

13. Civil Registries Data (CRD) (Deaths)

14. National Diabetes Audit (NDA)

15. Patient Reported Outcome Measures (PROMs)

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

Data Processor 1 - North of England Commissioning Support Unit (NECS)

1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs) is securely transferred from the DSCRO to North of England Commissioning Support Unit (NECS).

2. North of England Commissioning Support Unit (NECS) 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. North of England Commissioning Support Unit (NECS) then pass the processed, pseudonymised and linked data to the CCG.

5. Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit (NECS) or the CCG as instructed by the CCG.

6. Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

Data processor 2 - Methods Analytical Ltd

1) Pseudonymised SUS and Local Provider data, only is securely transferred from the DSCRO to North England CSU.

2) North of England Commissioning Support Unit (NECS) add derived fields, link data and provide analysis.

3) North England CSU also receives identifiable GP data from GP Practices. This data is kept secure and separate from any other data and is pseudonymised once it has entered the CSU. Any identifiable data is then destroyed.

4) North England CSU then securely pass the pseudonymised data to Methods Analytical Ltd for the addition of derived fields, linkage of data sets and analysis.

5) Allowed linkage is between the data sets contained within point 1 and point 3 (only once pseudonymised).

6) Methods Analytical Ltd also receive pseudonymised Social care data from providers.

7) Methods Analytical Ltd then link and process the pseudonymised data and 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.

8) Re-identification is only permitted for the purposes of direct care.

9) Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit (NECS) or the CCG as instructed by the CCG.

10) Patient level data will not be shared outside of the CCG and will only be shared within the CCG on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

Data Processor 3 - Sheffield Hallam University

1) Pseudonymised SUS and Local Provider data only is securely transferred from the DSCRO to North England CSU.

2) North of England Commissioning Support Unit (NECS) add derived fields, link data and provide analysis.

3) Allowed linkage is between the data sets contained within point 1.

4) North of England Commissioning Support Unit (NECS) then pass the processed, pseudonymised and linked data to the CCG.

5) The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.

6) The CCG then pass the pseudonymised data securely to Sheffield Hallam University to analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.

7) Aggregation of required data for CCG management use will be completed by Sheffield Hallam University as instructed by the CCG.

8) Patient level data will not be shared outside of Sheffield Hallam University and will only be shared within Sheffield Hallam University on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

Data Processor 4 - University of Sheffield

1) Pseudonymised SUS and Local Provider data only is securely transferred from the DSCRO to North England CSU.

2) North of England Commissioning Support Unit (NECS) add derived fields, link data and provide analysis.

3) Allowed linkage is between the data sets contained within point 1.

4) North of England Commissioning Support Unit (NECS) then pass the processed, pseudonymised and linked data to the CCG.

5) The CCG analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.

6) The CCG then pass the pseudonymised data securely to University of Sheffield to analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning.

7) Aggregation of required data for CCG management use will be completed by the University of Sheffield as instructed by the CCG.

8) Patient level data will not be shared outside of the University of Sheffield and will only be shared within the University of Sheffield on a need to know basis, as per the purposes stipulated within the Data Sharing Agreement. External aggregated reports only with small number suppression can be shared as set out within NHS Digital guidance applicable to each data set.

Data Processor 5 – Attain Health Management Services Ltd

1) Pseudonymised SUS and Local Provider data only is securely transferred from the DSCRO to North England CSU.

2) North of England Commissioning Support Unit (NECS) add derived fields, link data and provide analysis.

3) Allowed linkage is between the data sets contained within point 1.

4) North of England Commissioning Support Unit (NECS) then pass the processed, pseudonymised and linked data to Attain.

5) Attain analyse the data to see patient journeys for pathways or service design, re-design and de-commissioning and then send the pseudonymised data to the CCG

6) Aggregation of required data for CCG management use will be completed by Attain 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.

To maintain a consistent pseudonym across the processing for commissioning purposes, each Data Processor has deployed OpenPseudonymiser to develop project specific pseudonyms. Each data provider uses a shared SALT encryption to generate the specific pseudonyms for each provision of pseudonymised data. The SALT phrase is encrypted to avoid reidentification by any of the Data Processors.

INVOICE VALIDATION

1. The Controlled Environment for Finance (CEfF) will enable the CCG to challenge invoices and raise discrepancies and disputes.

2. Outputs from the CEfF will enable accurate production of budget reports, which will:

a. Assist in addressing poor quality data issues

b. Assist in business intelligence

3. Validation of invoices for non-contracted events where a service delivered to a patient by a provider that does not have a written contract with the patient’s responsible commissioner, but does have a written contract with another NHS commissioner/s.

4. Budget control of the CCG.

INVOICE VALIDATION - Liaison Financial Services Ltd

1. Validation of Continuing Healthcare related invoices and payments

2. Independent Identification of potential overpayments made by the CCG through invoice validation

3. Liaising with providers with a view to recouping these monies

4. Review is completed for the retrospective period from date of contract with Liaison Financial Services back to 01/04/2013.

5. Reviews take 3-9 months depending on number of claims to investigate and resolve

6. Liaison Financial Services would repeat the exercise 2-3 years later

7. CCGs could request reviews to be done more frequently

8. SUS+ would only be requested each time a review was completed, and could be requested at different times as independent reviews

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. 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.

CCGs will be able to:

3. Target specific vulnerable patient groups and enable clinicians with the duty of care for the patient to offer appropriate interventions.

4. Reduce hospital readmissions and targeting clinical interventions to high risk patients.

5. Identify patients at risk of deterioration and providing effective care.

6. Reduce in the difference in the quality of care between those with the best and worst outcomes.

7. Re-design care to reduce admissions.

8. Set up capitated budgets – budgets based on care provided to the specific population.

9. Identify health determinants of risk of admission to hospital, or other adverse care outcomes.

10. Monitor vulnerable groups of patients including but not limited to frailty, COPD, Diabetes, elderly.

11. Health needs assessments – identifying numbers of patients with specific health conditions or combination of conditions.

12. Classify vulnerable groups based on: disease profiles; conditions currently being treated; current service use; pharmacy use and risk of future overall cost.

13. Production of Theographs – a visual timeline of a patients encounters with hospital providers.

14. Analyse based on specific diseases

In addition:

- The risk stratification tool will provide aggregate reporting of number and percentage of population found to be at risk.

- Record level output (pseudonymised) will be available for commissioners (of the CCG), pseudonymised at patient level. Onward sharing of this data is not permitted.

COMMISSIONING

1. Commissioner reporting:

a. Summary by provider view - plan & actuals year to date (YTD).

b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD.

c. Summary by provider view - activity & finance variance by POD.

d. Planned care by provider view - activity & finance plan & actuals YTD.

e. Planned care by POD view - activity plan & actuals YTD.

f. Provider reporting.

g. Statutory returns.

h. Statutory returns - monthly activity return.

i. Statutory returns - quarterly activity return.

j. Delayed discharges.

k. Quality & performance referral to treatment reporting.

2. Readmissions analysis.

3. Production of aggregate reports for CCG Business Intelligence.

4. Production of project / programme level dashboards.

5. Monitoring of acute / community / mental health quality matrix.

6. Clinical coding reviews / audits.

7. Budget reporting down to individual GP Practice level.

8. GP Practice level dashboard reports include high flyers.

9. Comparators of CCG performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports

10. Data Quality and Validation measures allowing data quality checks on the submitted data

11. Contract Management and Modelling

12. Patient Stratification, such as:

o Patients at highest risk of admission

o Most expensive patients (top 15%)

o Frail and elderly

o Patients that are currently in hospital

o Patients with most referrals to secondary care

o Patients with most emergency activity

o Patients with most expensive prescriptions

o Patients recently moving from one care setting to another

i. Discharged from hospital

ii. Discharged from community

13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services.

14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die.

15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support.

16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust.

17. Removal of patients from Risk Stratification reports.

18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.

Specific outputs related to the work of the following Data Processors:

Data Processor 2 – Methods Analytical Ltd

1) The Methods Analytical Ltd processing will generate an output of predictive risk scores at the person level calculated from predictor parameters obtained from SUS, primary care and local flows.

2) The aim is to calculate a range of different predictive scores that would be useful to inform patients’ direct care, where validated algorithms are available. Such predictive scores would include the risk of hospital admission, electronic frailty index and the risk of admission to long term residential care.

3) The risk scores would be augmented with other contextual information relevant to the care process in the format of a care dashboard, such as diagnoses of long term conditions and relevant service activity.

Data Processor 3 – Sheffield Hallam University

1) The university undertakes commissioned projects on behalf of the CCG to evaluate pilots and similar schemes to inform commissioning / investment decisions – generally where the CCG does not have in-house expertise – and this will involve data processing and analytics. Generally, the CCG does not solely work with a single university data processor, because of a) Fair Trading considerations, and b) each university offers quite different specialisations and expertise, the specifics of which in relation to this application are set out below.

2) The general outputs from data processing by the university includes aggregated descriptive and interferential statistics to ascertain outcome and impact in such evaluations, as well as health economic descriptors to understand cost-utility or cost-effectiveness.

3) The CCG works with Sheffield Hallam University principally in relation to projects involving the healthcare workforce (as a training institution for nurses and therapy professions) and those involving community healthcare services.

4) Specific outputs will focus on the effectiveness and cost-effectiveness of options involving the healthcare professions and teams (most often the nursing and therapy workforce), multidisciplinary working, and community healthcare services.

Data Processor 4 – University of Sheffield

1) The university undertakes commissioned projects on behalf of the CCG to evaluate pilots and similar schemes to inform commissioning / investment decisions – generally where the CCG does not have in-house expertise – and this will involve data processing and analytics. Generally, the CCG does not solely work with a single university data processor, because of a) Fair Trading considerations, and b) each university offers quite different specialisations and expertise, the specifics of which in relation to this application are set out below.

2) The general outputs from data processing by the university includes aggregated descriptive and interferential statistics to ascertain outcome and impact in such evaluations, as well as health economic descriptors to understand cost-utility or cost-effectiveness.

3) The University of Sheffield, School of Health & Related Research (ScHARR) are partners in the Yorkshire & The Humber Collaboration for Leadership in Applied Health Research and Care (CLAHRC). This includes the evaluation on behalf of the CCG of several current and forthcoming national pilots taking place in the city.

4) The CCG works with the University of Sheffield principally in relation to mental health & wellbeing, secondary care services, urgent & emergency care, primary care services and health technologies.

5) Specific outputs will focus on the effectiveness and cost-effectiveness of options involving the services set out in item 2.

Data Processor 5 – Attain Health Management Services Ltd

1) Attain has been appointed to assist the CCG with its planning for Sustainability & Transformation Plans; work that is focused on Sheffield-based tertiary services having larger geographic catchments, principally acute stroke and children’s secondary care services.

2) Outputs from data processing will comprise consolidated activity and commissioner expenditure in relation to these services.

Data Processor 7 - Prescribing Services Ltd

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.

INVOICE VALIDATION

The invoice validation process supports the ongoing delivery of patient care across the NHS and the CCG region by:

1. Ensuring that activity is fully financially validated.

2. Ensuring that service providers are accurately paid for the patients treatment.

3. Enabling services to be planned, commissioned, managed, and subjected to financial control.

4. Enabling commissioners to confirm that they are paying appropriately for treatment of patients for whom they are responsible.

5. Fulfilling commissioners duties to fiscal probity and scrutiny.

6. Ensuring full financial accountability for relevant organisations.

7. Ensuring robust commissioning and performance management.

8. Ensuring commissioning objectives do not compromise patient confidentiality.

9. Ensuring the avoidance of misappropriation of public funds.

INVOICE VALIDATION - Liaison Financial Services Ltd

Expected measurable benefits to health and/or social care including target date:

1. Financial validation of activity

2. CCG Budget control

3. Assurances over the robustness of internal control mechanisms relating to the payment of invoices and/or suggested improvements

4. Identification and recovery of monies which would otherwise be lost

5. Meeting commissioning objectives without compromising patient confidentiality

6. The avoidance of misappropriation of public funds to ensure the ongoing delivery of patient care

7. Benefit delivered 3-9 months from receiving data, depending on number of claims to investigate and resolve

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

6. 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.

14. Providing greater understanding of the underlying courses and look to commission improved supportive networks, this would be ongoing work which would be continually assessed.

15. Insight to understand the numerous factors that play a role in the outcome for both datasets. The linkage will allow the reporting both prior to, during and after the activity, to provide greater assurance on predictive outcomes and delivery of best practice.

16. Provision of indicators of health problems, and patterns of risk within the commissioning region.

17. Support of benchmarking for evaluating progress in future years.

The CCG has realised the measurable benefits for the data collection and the provided data has enabled services to be delivered to match the population requirements whilst planning for future needs.

Listed below is a number of further yielded benefits for commissioning;

1. Monitoring In year projects

2. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients

3. Successful delivery of integrated care within the CCG.

4. Better understanding of the health of and the variations in health outcomes within the population to help understand local population characteristics.

5. Insights into patient outcomes, and identification of the possible efficacy of outcomes-based contracting opportunities.

The CCG will look to build on the yielded benefits of commissioning services that meet the needs of their local population, and that are effective in their delivery. The CCG will use intelligence to add insight to strategic commissioning and service integration across the CCG Area. This work will continue year on year to match the delivery/funding of targets services for the population within the CCG Area.

The continued access to this data will enable the CCG to further understand and improve service performance and delivery, including patient pathway design, re-design and patient experience.