DSfC - NHS North East Lincolnshire CCG; IV, RS & Comm.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

[5 paragraphs unchanged] 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 NHS North of England Commissioning Support Unit. [56 paragraphs unchanged]

Processing activities

[38 paragraphs unchanged] For the purpose of Risk Stratification: • Patients who are normally registered and/or resident within the NHS North East Lincolnshire CCG region (including historical activity where the patient was previously registered or resident in another commissioner [20 paragraphs unchanged] RISK STRATIFICATION 1. Identifiable SUS+ data is transferred 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 NHS North of England Commissioning Support Unit, who securely hold the SUS+. 3. Identifiable GP Data is securely sent from the GP system to NHS North of England Commissioning Support Unit. 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 NHS North of England Commissioning Support Unit has completed the processing, the CCG can access the online system via a secure connection to access the data pseudonymised at patient level [85 paragraphs unchanged]

Expected output

[7 paragraphs unchanged] 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. [52 paragraphs unchanged]

Expected measurable benefits

[11 paragraphs unchanged] 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 and health outcomes through more effective commissioning of services. [48 paragraphs unchanged]

Benefits reported

Stated in the previous version and removed here.

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.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + Adult Social Care; + Medicines dispensed in Primary Care (NHSBSA data)

Objective for processing

[2 paragraphs unchanged] 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 [17 words unchanged] 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. determining if the CCG is the responsible commissioner for the patient. [36 paragraphs unchanged] - Medicines Dispensed in Primary Care (NHSBSA Data) - Adult Social Care Data - Processing of the Medicines Dispensed in Primary Care (NHSBSA Data) dataset is only permitted to provide intelligence about the safety and effectiveness of medicines, as specified by the NHS Business Services Authority (NHSBSA) Medicines Data Directions 2019. [4 paragraphs unchanged] • Using value as the redesign principle [9 paragraphs unchanged]  Support measuring the health, mortality or care needs of the total local populatio population.  Provide intelligence about the safety and effectiveness of medicines.  Allow analysis of patient pathways across healthcare and social care. [3 paragraphs unchanged]

Processing activities

[11 paragraphs unchanged] 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. 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 [9 paragraphs unchanged] • Patients who are normally registered and/or resident within the NHS Northumberland North East Lincolnshire CCG region (including historical activity where the patient was previously registered or resident in another commissioner). [1 paragraph unchanged] • Patients treated by a provider where NHS Northumberland North East Lincolnshire CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the [9 words unchanged] is only for commissioning and relates to both national and local flows. [1 paragraph unchanged] • Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of NHS Northumberland North East Lincolnshire CCG - this is only for commissioning and relates to both national and local flows. [2 paragraphs unchanged] In addition to the dissemination of Cancer Waiting Times Data via the DSCRO, the CCG is able to access reports held within the CWT system in NHS Digital directly. Access within the CCG is limited to those with a need to process the data for the purposes described in this agreement. A CCG user will be able to access the provider extracts from the portal for any provider where at least 1 patient for whom they are the registered CCG for that individuals GP practice appears in that setting Although a CCG user may have access to pseudonymised patient information not related to that CCG, users should only process and analyse data for which they have a legitimate relationship (as described within Data Minimisation). [1 paragraph unchanged] North East Lincolnshire Council provide IT infrastructure for NHS North East Lincolnshire CCG 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. Microsoft Limited provide Cloud Services to NHS 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. [44 paragraphs unchanged] 19. Medicines Dispensed in Primary Care (NHSBSA Data) 20. Adult Social Care Data [8 paragraphs unchanged] 7. The DSCRO then pass the pseudonymised SUS, local provider data, Mental [43 words unchanged] (NDA), Patient Reported Outcome Measures (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and (PDS), Summary Hospital-level Mortality Indicator (SHMI) (SHMI), Medicines Dispensed in Primary Care (NHSBSA Data) and Adult Social Care data securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis. [42 paragraphs unchanged]

Expected output

[47 paragraphs unchanged] 19. Manage demand - demand, by understanding the quantity of assessments required, required CCGs are able to improve the care service for patients by predicting [7 words unchanged] ensure the secondary care system has enough capacity to manage the demand. 20. In monitoring the quality of referrals under current structures, CCGs are able to observe Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 21. CCGs may identify Identify low priority procedures which could be directed to community-based alternatives and as [6 words unchanged] referrals for low priority procedures resulting in a reduction in hospital referrals. 22. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand. 22. Allow Commissioners to better protect or improve the public health of the total local patient population 23. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand. 23. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population 24. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 24. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 25. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals. 25. Investigate mortality outcomes for trusts. 26. Allow Commissioners to better protect or improve the public health of the total local patient population 26. Identify medication prescribing trends and their effectiveness. 27. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population 27. Linking prescribing habits to entry points into the health and social care system 28. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 28. Identify, quantify and understand cohorts of patient’s high numbers of different medications (polypharmacy) 29. Investigate mortality outcomes for trusts 29. Monitoring, at a population level, particular cohorts of service users and designing analytical models which support more effective interventions in health and adult social care 30. Monitoring service and integrated care outcomes across a pathway or care setting involving adult social care

Expected measurable benefits

[46 paragraphs unchanged] 19. Assists commissioners to make better decisions to support patients and drive changes in health care 20. Help drive changes in healthcare 20. Allows comparisons of providers performance to assist improvement in services – increase the quality 21. Allows comparisons of providers performance to assist improvement in services – increase the quality 21. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 22. Inform commissioners and improve services 22. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 23. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 23. Monitoring of entire population, as opposed to only those that engage with services 24. Understanding the interdependency of care services 24. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice. 25. Targeting care more effectively 25. Monitor the quality and safety of the delivery of healthcare services. 26. Using value as the redesign principle 26. Allow focused commissioning support based on factual data rather than assumed and projected sources 27. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them 27. Understand admissions linked to overprescribing. 28. 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 28. Add value to the population health management workstream by adding prescribing data into linked dataset for segmentation and stratification. 29. 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 29. Developing, through evaluation of person-level data, more effective prevention strategies and interventions across a pathway or care setting involving adult social care 30. Service redesign 30. Designing and implementing new payment models across health and adult social care 31. Health Needs Assessment – identification of underlying disease prevalence within the local population 31. Understanding current and future population needs and resource utilisation for local strategic planning and commissioning purposes including for health, social care and public health needs. 32. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 33. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 34. Assists commissioners to make better decisions to support patients and drive changes in health care 35. Allows comparisons of providers performance to assist improvement in services – increase the quality 36. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 37. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 38. Monitoring of entire population, as a pose to only those that engage with services 39. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice. 40. Monitor the quality and safety of the delivery of healthcare services. 41. Allow focused commissioning support based on factual data rather than assumed and projected sources

Benefits reported

Not stated in the previous version; added here.

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.

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Datasets: + Personal Demographic Service; + Summary Hospital-level Mortality Indicator (SHMI); + e-Referral Service for Commissioning

Objective for processing

[36 paragraphs unchanged] - e-Referral Service (eRS) - Personal Demographics Service (PDS) - Summary Hospital-level Mortality Indicator (SHMI) [12 paragraphs unchanged]  Patient stratification and predictive modelling - to highlight patients cohorts of people at risk of requiring hospital admission and other avoidable factors such as [6 words unchanged] executed against linked de-identified data, and identification of future service delivery models  Demand Management - to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand.  Support measuring the health, mortality or care needs of the total local populatio [3 paragraphs unchanged]

Processing activities

[29 paragraphs unchanged] Microsoft Limited and Amazon Web Services both provide Cloud Services to Optum Health Solutions UK Limited 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. [40 paragraphs unchanged] 16. e-Referral Service (eRS) 17. Personal Demographics Service (PDS) 18. Summary Hospital-level Mortality Indicator (SHMI) [8 paragraphs unchanged] 7. The DSCRO then pass the pseudonymised SUS, local provider data, Mental [31 words unchanged] Times Monitoring Data Set (CWT), Civil Registries Data (CRD), National Diabetes Audit (NDA) and (NDA), Patient Reported Outcome Measures (PROMs) (PROMs), e-Referral Service (eRS), Personal Demographics Service (PDS) and Summary Hospital-level Mortality Indicator (SHMI) data securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis. [42 paragraphs unchanged]

Expected output

[47 paragraphs unchanged] 19. Manage demand - by understanding the quantity of assessments required, CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand. 20. In monitoring the quality of referrals under current structures, CCGs are able to observe the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 21. CCGs may identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals. 22. Using pseudonymised e-RS data to provide intelligence will support the understanding of the quantity of assessments required and demand management. CCGs will be able to improve the care service for patients by predicting the impact on certain care pathways and support the secondary care system in ensuring enough capacity to manage the demand. 23. Manage demand, by understanding the quantity of assessments required CCGs are able to improve the care service for patients by predicting the impact on certain care pathways and ensure the secondary care system has enough capacity to manage the demand. 24. Monitor the timing of key actions relating to referral letters. CCG’s are unable to see the contents of the referral letters. 25. Identify low priority procedures which could be directed to community-based alternatives and as such commission these services and deflect referrals for low priority procedures resulting in a reduction in hospital referrals. 26. Allow Commissioners to better protect or improve the public health of the total local patient population 27. Allow Commissioners to plan, evaluate and monitor health and social care policies, services, or interventions for the total local patient population 28. Allow Commissioners to compare their providers (trusts) mortality outcomes to the national baseline. 29. Investigate mortality outcomes for trusts

Expected measurable benefits

[45 paragraphs unchanged] 18. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 19. Assists commissioners to make better decisions to support patients 20. Help drive changes in healthcare 21. Allows comparisons of providers performance to assist improvement in services – increase the quality 22. Inform commissioners and improve services 23. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 24. Understanding the interdependency of care services 25. Targeting care more effectively 26. Using value as the redesign principle 27. Thoroughly investigating the needs of the population, to ensure the right services are available for individuals when and where they need them 28. 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 29. 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 30. Service redesign 31. Health Needs Assessment – identification of underlying disease prevalence within the local population 32. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 33. Allow reporting to drive changes and improve the quality of commissioned services and health outcomes for people. 34. Assists commissioners to make better decisions to support patients and drive changes in health care 35. Allows comparisons of providers performance to assist improvement in services – increase the quality 36. Allow analysis of health care provision to be completed to support the needs of the health profile of the population within the CCG area based on the full analysis of multiple pseudonymised datasets. 37. To evaluate the impact of new services and innovations (e.g. if commissioners implement a new service or type of procedure with a provider, they can evaluate whether it improves outcomes for patients compared to the previous one). 38. Monitoring of entire population, as a pose to only those that engage with services 39. Enable Commissioners to be able to see early indications of potential practice resilience issues in that an early warning marker can often be a trend of patients re-registering themselves at a neighbouring practice. 40. Monitor the quality and safety of the delivery of healthcare services. 41. Allow focused commissioning support based on factual data rather than assumed and projected sources

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

[2 paragraphs unchanged] Invoices are submitted to the Clinical Commissioning Group (CCG) so they the CCG is are able to ensure that the activity claimed for each patient is [37 words unchanged] NHS number is only used to confirm the accuracy of backing-data sets (data from providers) and will not be used further. Invoice Validation with be conducted by NHS North of England Commissioning Support Unit. The CCG are advised by the appointed CEfF whether payment for invoices can be made or not. The CCG are advised Invoice Validation with be conducted by NHS North of England Commissioning Support Unit whether payment for invoices can be made or not. Unit. [24 paragraphs unchanged] - Community Services Data Set (CSDS) [1 paragraph unchanged] -           Community Services Data Set (CSDS) [1 paragraph unchanged] - Civil Registries Data – Births and Deaths (CRD) (Births) - Civil Registries Data (CRD) (Deaths) [14 paragraphs unchanged]  Patient stratification and predictive modelling - to identify specific highlight patients at risk of requiring hospital admission and other avoidable factors such [7 words unchanged] executed against linked de-identified data, and identification of future service delivery models In addition, NHS North of England Commissioning Support Unit also receive pseudonymised GP data and Social Care data. This is pseudonymised either at source or within NHS North of England Commissioning Support Unit acting as a data processor on behalf of each data controller. This pseudonymisation process is different to that within the DSCRO. Also, each data source will use a variation of this process so there is no linkage between these data until a common pseudonym has been applied via the DSCRO. 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. Patient data historically sits in silos within various NHS services. Linking datasets including GP data social care and other datasets enables commissioners to fully understand the effective delivery of health and social care services for the populations they manage and not just for those directly receiving treatment. It supports commissioners to allocate resources as well as providing greater insight into the provision of services and to the health of the population. Processing for commissioning will be conducted by North of England Commissioning Support Unit and Optum Health Solutions (UK) Ltd. Linking primary, secondary, community care data supports with understanding a full patient’s journey across their pathway and across the community which can provide opportunities for understanding health needs pre and post treatment across numerous health services In addition, North of England Commissioning Support Unit also receive pseudonymised GP data and Social Care data. This is pseudonymised either at source or within North of England Commissioning Support Unit. This pseudonymisation tool is different to that held within the DSCRO. Also, each data source will use a variation of this tool so there is no linkage between these data until a common pseudonym has been applied via the DSCRO. For example, analysis has shown that those able to manage their health conditions (GP data) are less likely to attend A&E and less likely to be admitted in an emergency (secondary care data). It can also support with coordinating discharge planning and integration of services as those receiving social care can be a key driver of demand for health and care. Processing for commissioning will be conducted by NHS North of England Commissioning Support Unit.

Processing activities

PROCESSING CONDITIONS: [3 paragraphs unchanged] All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role. role and the tasks that they are required to undertake. [1 paragraph unchanged] NHS Digital reminds all organisations party to this agreement of the need [32 words unchanged] and contractors of the Data Recipient who may have access to that data). data) Onward Sharing 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. 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: [2 paragraphs unchanged] Segregation SEGREGATION: [4 paragraphs unchanged] Data Minimisation DATA MINIMISATION: Data Minimisation in relation to the data sets listed within section 3 the application are listed below. This also includes the purpose on which they would be applied - [1 paragraph unchanged] • Patients who are normally registered and/or resident within the NHS East Riding of Yorkshire Northumberland CCG region (including historical activity where the patient was previously registered or resident in another commissioner). [1 paragraph unchanged] • Patients treated by a provider where NHS East Riding of Yorkshire Northumberland CCG is the host/co-ordinating commissioner and/or has the primary responsibility for the [9 words unchanged] is only for commissioning and relates to both national and local flows. [1 paragraph unchanged] • Activity identified by the provider and recorded as such within national systems (such as SUS+) as for the attention of NHS East Riding of Yorkshire Northumberland CCG - this is only for commissioning and relates to both national and local flows. [1 paragraph unchanged] • Patients who are resident and/or registered within the NHS East Riding of Yorkshire CCG region. Pulsant and IT Professional Services Ltd do not access data held under this agreement as they only supply [19 words unchanged] agreement. This includes granting of access to the database[s] containing the data. [2 paragraphs unchanged] 2. The DSCRO pushes a one-way data flow of SUS+ data into the Controlled Environment for Finance (CEfF) in the NHS North of England Commissioning Support Unit. [1 paragraph unchanged] 4. NHS North of England Commissioning Support Unit carry out the following processing activities within the CEfF for invoice validation purposes: a. Validating that the Clinical Commissioning Group is 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 [10 words unchanged] access and reports provided by NHS Digital to confirm the payments are: [3 paragraphs unchanged] 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 NHS North of England Commissioning Support Unit CEfF team and the provider provider, meaning that no identifiable data needs to be sent to the CCG. [8 words unchanged] management reporting detailing the total quantum of invoices received pending, processed etc. [2 paragraphs unchanged] 1. SUS SUS+ [1 paragraph unchanged] o a. Acute o b. Ambulance o c. Community o d. Demand for Service o e. Diagnostic Service o f. Emergency Care o g. Experience, Quality and Outcomes o h. Mental Health o i. Other Not Elsewhere Classified o j. Population Data o k. Primary Care Services o l. Public Health Screening [8 paragraphs unchanged] 11. National Cancer Waiting Times Monitoring Data Set (CWT) 12. Civil Registries Data – Births and Deaths (CRD) (Births) 13. National Diabetes Audit (NDA) 13. Civil Registries Data (CRD) (Deaths) 14. Patient Reported Outcome Measures (PROMs) 14. National Diabetes Audit (NDA) 15. Patient Reported Outcome Measures (PROMs) [1 paragraph unchanged] 1.         Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT) and Civil Registries Data – Births and Deaths (CRD), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs) only is securely transferred from the DSCRO to North of England Commissioning Support Unit. Data Processor 1 – North of England Commissioning Support Unit (CSU) 2.         North of England Commissioning Support Unit also receive pseudonymised GP Data and Social Care data. (See i – viii for detail) 1. Data quality management and pseudonymisation of data is completed by the DSCRO and the pseudonymised data is then held until completion of points 2 – 7. 3.         North of England Commissioning Support Unit add derived fields and link data. Data is stored on a server held within North of England Commissioning Support Unit. 2. North of England Commissioning Support Unit also receive GP Data and Social Care Data (See i – ix for detail) 4.         North of England Commissioning Support Unit provide analysis to: 3. Once the pseudonymised GP data and social care data is received, the CSU make a request to the DSCRO. a.         See patient journeys for pathways or service design, re-design and de-commissioning. 4. The DSCRO then send a mapping table to the CSU b.         Check recorded activity against contracts or invoices and facilitate discussions with providers. 5. The CSU then overwrite the organisation specific keys with the DSCRO key. c.         Undertake population health management 6. The mapping table is then deleted. d.         Undertake data quality and validation checks 7. The DSCRO then pass the pseudonymised SUS, local provider data, Mental Health (MHSDS, MHMDS, MHLDDS), Maternity (MSDS), Improving Access to Psychological Therapies (IAPT), Child and Young People’s Health (CYPHS) and Diagnostic Imaging (DIDS) Community Services Data Set (CSDS) , National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs) securely to North of England CSU for the addition of derived fields, linkage of data sets and analysis. e.         Thoroughly investigate the needs of the population 8. Social care and GP data is then linked to the data sets listed within point 7 in the CSU, utilising algorithms and analysis f.          Understand cohorts of residents who are at risk 9. North of England Commissioning Support provide analysis to: g.         Conduct Health Needs Assessments o See patient journeys for pathways or service design, re-design and de-commissioning. 5.         North of England Commissioning Support Unit also apply a risk stratification algorithm to pseudonymised SUS+, Local Provider flow and GP data only. Outputs are made available to North of England Commissioning Support Unit and CCG analysts. o Check recorded activity against contracts or invoices and facilitate discussions with providers. 6.         Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit as instructed by the CCG. o Undertake population health management 7.         Patient level data will not be shared outside of the Data Processor/Controller and will only be shared within the Data Processors 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. o Undertake data quality and validation checks 8.       The CCG securely transfer pseudonymised commissioning data back to the provider to: o Thoroughly investigate the needs of the population o Understand cohorts of residents who are at risk o Conduct Health Needs Assessments 10. North of England Commissioning Support also apply an risk stratification algorithm to the pseudonymised SUS+, Local Provider flows and GP data. 11. Aggregation of required data for CCG management use will be completed by the CSU as instructed by the CCG. 12. Patient level data will not be shared outside of the Data Processor/Controller and will only be shared within the Data Processors 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. 13. The CCG securely transfer pseudonymised commissioning data back to the provider to: [4 paragraphs unchanged] The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider. Data Processor 2 - Optum Health Solutions (UK) Ltd All access to the North of England Commissioning Support Unit server is managed via Role Based Access Controls. 1. Pseudonymised SUS, Primary Care data, Mental Health Services Data Set and Community Services Data Set is securely transferred from North of England Commissioning Support to Optum Health Solutions (UK) Ltd. North of England Commissioning Support Unit have individual data processing agreements in place with GPs, Local Authorities and the CCG, to pseudonymise data. Acting on their behalf, North of England Commissioning Support Unit pseudonymises the data as follows: 2. Optum Health Solutions (UK) Ltd add derived fields, link SUS fields and provide analysis to: i. Identifiable GP and Social Care is submitted to North of England Commissioning Support Unit. o See patient journeys for pathways or service design, re-design and de-commissioning. o Check recorded activity against contracts or invoices and facilitate discussions with providers (CCG). o Undertake population health management o Undertake data quality and validation checks o Thoroughly investigate the needs of the population o Understand cohorts of residents who are at risk o Conduct Health Needs Assessments 3. Allowed linkage is between the data sets contain within point 1 4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG. 5. Aggregation of required data for CCG management use will be completed by Optum Health Solutions (UK) Ltd 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. 7. Optum Health Solutions (UK) Ltd will only be in receipt of data and only be permitted to act as Data Processors for the period specified in the contract with the CCG. North of England Commissioning Support Unit have individual data processing agreements in place with GPs, Local Authorities and the CCGs, to pseudonymise data. Acting on their behalf, North of England Commissioning Support Unit pseudonymises the data as follows: i. Identifiable GP and Social Care data is submitted to North of England Commissioning Support Unit. [8 paragraphs unchanged]

Expected output

[26 paragraphs unchanged] 8. GP Practice level dashboard reports include high flyers. reports. 9.         All of the above segmented in to population groups 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.       Analysis across health and social care by patient (outputs aggregated) providing a greater understand of service interdependencies and opportunities for a single service delivery model where overlap may exist currently 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11.       Variation reporting between primary and secondary care (e.g. where one care setting suggests the patient has a condition but the other does not potentially leading to inappropriate treatment) 11. Contract Management and Modelling 12.       Delayed transfers of care analysis 12. Patient Stratification, such as: o Patients at highest risk of admission o High cost activity uses (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community 13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services. 14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die. 15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support. 16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust. 17. Removal of patients from Risk Stratification reports. 18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.

Expected measurable benefits

[16 paragraphs unchanged] d.         Pooled health and social care budget reporting 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 2.         Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types and patient groups [8 paragraphs unchanged] b. Financial and Non-financial validation of activity. [6 paragraphs unchanged] i. Understanding the care of patients in nursing homes and social care. homes. [1 paragraph unchanged] 7.         New commissioning and service delivery models delivered via joint health and social care teams reducing duplication 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.         Reduction in variation of outcomes and quality of care through increased understanding of primary and secondary care interaction. E.g. if cancer treatment outcomes are poor in one area does the GP data indicate a delayed referral? 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.         A complete understanding of service utilisation to aid capacity/demand planning across health and social 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.       Early warning of likely pressures in the wider health and system following increased activity in primary and social care giving other providers a chance to plan and react. 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.