NHS Digital Data Release Register - reformatted

NHS North of England Commissioning Support Unit

Project 1 — DARS-NIC-349688-V6V0Q

Opt outs honoured: No - data flow is not identifiable (Does not include the flow of confidential data)

Sensitive: Sensitive

When: 2020/03 — 2020/07.

Repeats: Frequent Adhoc Flow

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

Categories: Anonymised - ICO code compliant

Datasets:

  • Acute-Local Provider Flows
  • Ambulance-Local Provider Flows
  • Children and Young People Health
  • Civil Registration - Births
  • Civil Registration - Deaths
  • Community Services Data Set
  • Community-Local Provider Flows
  • Demand for Service-Local Provider Flows
  • Diagnostic Imaging Dataset
  • Diagnostic Services-Local Provider Flows
  • Emergency Care-Local Provider Flows
  • Experience, Quality and Outcomes-Local Provider Flows
  • Improving Access to Psychological Therapies Data Set
  • Maternity Services Data Set
  • Mental Health and Learning Disabilities Data Set
  • Mental Health Minimum Data Set
  • Mental Health Services Data Set
  • Mental Health-Local Provider Flows
  • National Cancer Waiting Times Monitoring DataSet (CWT)
  • National Diabetes Audit
  • Other Not Elsewhere Classified (NEC)-Local Provider Flows
  • Patient Reported Outcome Measures
  • Population Data-Local Provider Flows
  • Primary Care Services-Local Provider Flows
  • Public Health and Screening Services-Local Provider Flows
  • SUS for Commissioners

Objectives:

COMMISSIONING To use pseudonymised data to provide intelligence to support the commissioning of health services. The data (containing both clinical and financial information) is analysed so that health care provision can be planned to support the needs of the population within the CCG area. The CCGs commission services from a range of providers covering a wide array of services. Each of the data flow categories requested supports the commissioned activity of one or more providers. The following pseudonymised datasets are required to provide intelligence to support commissioning of health services: - Secondary Uses Service (SUS+) - Local Provider Flows o Acute o Ambulance o Community o Demand for Service o Diagnostic Service o Emergency Care o Experience, Quality and Outcomes o Mental Health o Other Not Elsewhere Classified o Population Data o Primary Care Services o Public Health Screening - Mental Health Minimum Data Set (MHMDS) - Mental Health Learning Disability Data Set (MHLDDS) - Mental Health Services Data Set (MHSDS) - Maternity Services Data Set (MSDS) - Improving Access to Psychological Therapy (IAPT) - Child and Young People Health Service (CYPHS) - Community Services Data Set (CSDS) - Diagnostic Imaging Data Set (DIDS) - National Cancer Waiting Times Monitoring Data Set (CWT) - Civil Registries Data (CRD) (Births) - Civil Registries Data (CRD) (Deaths) - National Diabetes Audit (NDA) - Patient Reported Outcome Measures (PROMs) 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 highlight 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. 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 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. Processing for commissioning will be conducted by North of England Commissioning Support Unit, Optum Health Solutions UK Limited and Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium). The eMBED Health Consortium is made up of 4 partners: Kier Group - Kier Business Services Limited • Dr Foster Limited • BDO • Engine Only two of the organisations process and store data (host the eMBED Health Consortium). BDO and Engine do not process, store or have access to any data. eMBED are not a legal entity, although they do have an IG Toolkit. Kier and Dr Foster Limited are the relevant legal entities hosting the eMBED Health Consortium.

Expected Benefits:

COMMISSIONING 1. Supporting Quality Innovation Productivity and Prevention (QIPP) to review demand management, integrated care and pathways. a. Analysis to support full business cases. b. Develop business models. c. Monitor In year projects. 2. Supporting Joint Strategic Needs Assessment (JSNA) for specific disease types. 3. Health economic modelling using: a. Analysis on provider performance against 18 weeks wait targets. b. Learning from and predicting likely patient pathways for certain conditions, in order to influence early interventions and other treatments for patients. c. Analysis of outcome measures for differential treatments, accounting for the full patient pathway. d. Analysis to understand emergency care and linking A&E and Emergency Urgent Care Flows (EUCC). 4. Commissioning cycle support for grouping and re-costing previous activity. 5. Enables monitoring of: a. CCGs' outcome indicators. b. Financial and Non-financial validation of activity. c. Successful delivery of integrated care within the CCGs. 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 CCGs' 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.

Outputs:

COMMISSIONING 1. Commissioner reporting: a. Summary by provider view - plan & actuals year to date (YTD). b. Summary by Patient Outcome Data (POD) view - plan & actuals YTD. c. Summary by provider view - activity & finance variance by POD. d. Planned care by provider view - activity & finance plan & actuals YTD. e. Planned care by POD view - activity plan & actuals YTD. f. Provider reporting. g. Statutory returns. h. Statutory returns - monthly activity return. i. Statutory returns - quarterly activity return. j. Delayed discharges. k. Quality & performance referral to treatment reporting. 2. Readmissions analysis. 3. Production of aggregate reports for CCGs' Business Intelligence. 4. Production of project / programme level dashboards. 5. Monitoring of acute / community / mental health quality matrix. 6. Clinical coding reviews / audits. 7. Budget reporting down to individual GP Practice level. 8. GP Practice level dashboard reports. 9. Comparators of CCGs' performance with similar CCGs as set out by a specific range of care quality and performance measures detailed activity and cost reports 10. Data Quality and Validation measures allowing data quality checks on the submitted data 11. Contract Management and Modelling 12. Patient Stratification, such as: o Patients at highest risk of admission o High cost activity uses (top 15%) o Frail and elderly o Patients that are currently in hospital o Patients with most referrals to secondary care o Patients with most emergency activity o Patients with most expensive prescriptions o Patients recently moving from one care setting to another i. Discharged from hospital ii. Discharged from community 13. Validation for payment approval, ability to validate that claims are not being made after an individual has died, like Oxygen services. 14. Validation of programs implemented to improve patient pathway e.g. High users unable to validate if the process to help patients find the best support are working or did the patient die. 15. Clinical - understand reasons why patients are dying, what additional support services can be put in to support. 16. Understanding where patient are dying e.g. are patients dying at hospitals due to hospices closing due to Local authorities withdrawing support, or is there a problem at a particular trust. 17. Removal of patients from Risk Stratification reports. 18. Re births provide a one stop shop of information, Births are recorded in multiple sources covering hospital and home births, a chance to overlook activity.

Processing:

PROCESSING CONDITIONS: Data must only be used for the purposes stipulated within this Data Sharing Agreement. Any additional disclosure / publication will require further approval from NHS Digital. Data Processors must only act upon specific instructions from the Data Controller. Data can only be stored at the addresses listed under storage addresses. All access to data is managed under Role-Based Access Controls. Users can only access data authorised by their role and the tasks that they are required to undertake. Patient level data will not be linked other than as specifically detailed within this Data Sharing Agreement. Data released will only be shared with those parties listed and will only be used for the purposes laid out in the application/agreement. NHS Digital reminds all organisations party to this agreement of the need to comply with the Data Sharing Framework Contract requirements, including those regarding the use (and purposes of that use) by “Personnel” (as defined within the Data Sharing Framework Contract ie: employees, agents and contractors of the Data Recipient who may have access to that data) ONWARD SHARING: 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. Aggregated reports only with small number suppression can be shared externally as set out within NHS Digital guidance applicable to each data set. SEGREGATION: Where the Data Processor and/or the Data Controller hold both identifiable and pseudonymised data, the data will be held separately so data cannot be linked. Where the Data Processor and/or the Data Controller hold identifiable data with opt outs applied and identifiable data with opt outs not applied, the data will be held separately so data cannot be linked. All access to data is auditable by NHS Digital. DATA MINIMISATION: Data Minimisation in relation to the data sets listed within the application are listed below. This also includes the purpose on which they would be applied - For the purpose of Commissioning: • Patients who are normally registered and/or resident within NHS North Lincolnshire CCG, NHS East Riding of Yorkshire or NHS Hull CCGs' regions (including historical activity where the patient was previously registered or resident in another commissioner). and/or • Patients treated by a provider where NHS North Lincolnshire CCG, NHS East Riding of Yorkshire or NHS Hull CCG 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 NHS North Lincolnshire CCG, NHS East Riding of Yorkshire and NHS Hull CCG - this is only for commissioning and relates to both national and local flows. N3i Limited supply IT infrastructure for 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. Calderdale and Huddersfield NHS Foundation Trust, Telecity, Telstra and Pulsant and IT Professional Services Ltd do not access data held under this agreement as they only supply the building. 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 UK 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. COMMISSIONING The Data Services for Commissioners Regional Office (DSCRO) obtains the following data sets: 1. SUS+ 2. Local Provider Flows (received directly from providers) a. Acute b. Ambulance c. Community d. Demand for Service e. Diagnostic Service f. Emergency Care g. Experience, Quality and Outcomes h. Mental Health i. Other Not Elsewhere Classified j. Population Data k. Primary Care Services l. Public Health Screening 3. Mental Health Minimum Data Set (MHMDS) 4. Mental Health Learning Disability Data Set (MHLDDS) 5. Mental Health Services Data Set (MHSDS) 6. Maternity Services Data Set (MSDS) 7. Improving Access to Psychological Therapy (IAPT) 8. Child and Young People Health Service (CYPHS) 9. Community Services Data Set (CSDS) 10. Diagnostic Imaging Data Set (DIDS) 11. National Cancer Waiting Times Monitoring Data Set (CWT) 12. Civil Registries Data (CRD) (Births) 13. Civil Registries Data (CRD) (Deaths) 14. National Diabetes Audit (NDA) 15. Patient Reported Outcome Measures (PROMs) Data quality management and pseudonymisation is completed within the DSCRO and is then disseminated as follows: Data Processor 1 – NHS North of England Commissioning Support Unit 1. Pseudonymised SUS+, Local Provider data, Mental Health data (MHSDS, MHMDS, MHLDDS), Maternity data (MSDS), Improving Access to Psychological Therapies data (IAPT), Child and Young People’s Health data (CYPHS), Community Services Data Set (CSDS), Diagnostic Imaging data (DIDS), National Cancer Waiting Times Monitoring Data Set (CWT), Civil Registries Data (CRD) (Births and Deaths), National Diabetes Audit (NDA) and Patient Reported Outcome Measures (PROMs) only is securely transferred from the DSCRO to North of England Commissioning Support Unit. 2. North of England Commissioning Support Unit also receive pseudonymised GP Data and Social Care data. (See i – viii for detail) 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. 4. Access to the North of England Commissioning Support Unit server (data listed in point 1 and 2 only) is granted to Kier Business Services Limited (Hosting the eMBED Health Consortium) via Role Based Access Control analyse the data and then to Dr Foster Limited (Hosting the eMBED Health Consortium). Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium) provide analysis as point 5 and between them produce different reports, utilising different techniques, to produce the outputs listed at point 5. 5. North of England Commissioning Support Unit and Kier Business Services Limited and Dr. Foster Limited (Hosting the eMBED Health Consortium) 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 6. 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 analysts and Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium). 7. Aggregation of required data for CCG management use will be completed by North of England Commissioning Support Unit and/or Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium) as instructed by the CCGs. 8. 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. 9. Kier Business Services Limited and Dr Foster Limited (Hosting the eMBED Health Consortium) and the CCGs are permitted to download data in points 1 and 2 to their servers and outputs from point 6. 10. The CCG securely transfer Pseudonymised data back to the provider to: a) confirm how patients are reported in SUS, and how the commissioner can reliably group these patients into categories for points of delivery; b) allow for granular data validation whereby a commissioner may query the SUS record, and need to pass it back to the provider for checking; and c) to allow the provider to undertake further analysis of a cohort of their patients as requested and specified by the commissioner. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider. Kier Business Services Limited and Dr Foster (Hosting the eMBED Health Consortium) will not have access to the pseudonymisation tool or encryption key used for the data, therefore is unable to re-identify the data effectively rendering the data anonymous. All access to the North of England Commissioning Support Unit server is managed via Role Based Access Controls. Commissioning - Data Processor - Optum Health Solutions (UK) Ltd 1. Pseudonymised SUS, Local Provider Data, Social Care Data, Mental Health Services Dataset, Community Services Dataset and GP Primary Care data is securely transferred from North of England Commissioning Support Unit to Optum Health Solutions (UK) Ltd. The data is decoupled from the other national datasets and sent as individual data flows 2. Optum Health Solutions (UK) Ltd provide analysis to: Whole population segmentation to assess population health needs Prospective risk scoring for individuals to indicate the likelihood of future adverse events Predictive modelling to determine individuals at risk and an understanding of the drivers of risk Longitudinal analysis of intersegmental drift Identifying individuals who move between complexity classifications and the drivers of these transitions The production of individual-level theographs to identify gaps in care 3. Allowed linkage is between the datasets contained within point (1) above. GP and Social Care datasets are needed for the processing carried out by Optum to enhance the population health analytics beyond SUS and LPF's which contain only secondary care activity 4. Optum Health Solutions (UK) Ltd then pass the processed, pseudonymised and linked data to the CCG. 5. Aggregates 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 as set out within NHS Digital guidance applicable to each data set. 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 CCGs. The data transferred to the provider is only that which relates directly to the data previously uploaded by that particular provider. 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. ii. The data lands in a ring-fenced area. iii. North of England Commissioning Support Unit has access to a pseudonymisation tool. North of England Commissioning Support Unit requests an organisation specific pseudonymisation key from the DSCRO. The key can only be used once. The key is specific to the individual request and the organisation it is being requested for. iv. The data is then pseudonymised using the organisation specific pseudonymisation tool and DSCRO issued key. The identifiable data is then deleted from the ring-fenced area. v. To enable linkage to data listed in point 1, North of England Commissioning Support Unit make a request to the DSCRO. vi. The DSCRO then send a mapping table to North of England Commissioning Support Unit. vii. A black box uses the mapping table to overwrite the organisation specific pseudonym with the DSCRO pseudonym to enable linkage to NHS Digital released products (under this agreement). viii. The mapping table if then deleted. ix. In addition, for social care data only: Social Care organisations have access to the pseudonymisation tool and can request an organisation specific pseudonymisation key from the DSCRO. The key can only be used once and is specific to that date. The organisation then submits the pseudonymised social care data to North of England Commissioning Support Unit. The data then follows from point v.


Project 2 — DARS-NIC-08095-P4D0D

Opt outs honoured: No - data flow is not identifiable

Sensitive: Non Sensitive

When: 2016/04 (or before) — 2019/02.

Repeats: Ongoing

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

Categories: Anonymised - ICO code compliant

Datasets:

  • Hospital Episode Statistics Accident and Emergency
  • Hospital Episode Statistics Admitted Patient Care
  • Hospital Episode Statistics Critical Care
  • Hospital Episode Statistics Outpatients

Objectives:

NHS North of England Commissioning Support (NECS) provides a comprehensive business intelligence (BI) service to a wide range of NHS organisations. This includes both standard analytics and reporting, and deep-dives and diagnostic exercises to offer insight and intelligence on a commissioner’s health economy. In addition NECS offer a mature business intelligence application (RAIDR) allowing self-service access to a range of dashboards and configurable reports. This tool is available on a subscription basis only to NHS organisations and local authorities. It is currently used by Clinical Commissioning Groups (CCGs), internally within the CSU through specialist support teams and by CCG member practices. A list of current customers is attached as a supporting document (SD1). Both the business intelligence team and RAIDR utilise data feeds from secondary and community care, mental health services, urgent and primary care, prescribing and other HSCIC published datasets such as QOF, RTT etc. These data sets are provided either by the DSCRO service, downloaded directly the NHS England data catalogue or directly from provider organisations. Data delivered via the DSCRO is pseudonymised in to the CSU where the BI service and RAIDR are hosted. Published data is downloaded in aggregate form from HSCIC and NHS England websites. There will be no direct linkage between HES data records and other data already used by the CSU and in its BI tool (RAIDR). HES data may be presented alongside other data but not linked to it – for example a report may contain HES data alongside workforce statistics, weather reports etc. Typical uses for the business intelligence service and tool include • Provision of contract, performance and quality monitoring of commissioned services – this ensures CCGs are empowered with intelligence on the services they are accountable for and can undertake their statutory duties • Fully embrace clinical commissioning – CCGs have taken steps to delegate their some of their commissioning responsibility to their member practices. The RAIDR tool is used to present practice level activity and performance information allowing GP practices to assess how their local initiatives affect wider service utilization. For example, does opening their surgery later in the evening reduce the burden on A&E? Can they evidence a change in A&E usage from the point they opened later? • The national drive to progress the Better Care Fund and Vanguard alternate care models both require in-depth analytics. Access to timely information showing the impact of service transformations is key to evidencing the success of these national NHS programmes. • To support the on-going budgetary pressures the NHS is faced the business intelligence service and RAIDR offer significant support to commissioners on their QIPP programmes. Identifying service areas where the commissioner is an outlier that may then require re-procurement of a clinical service, comparisons with peer groups and best practice to understand how a change in approach might deliver a financial saving NECS is requesting HES data that will enable users of their business intelligence service and the RAIDR tool to compare themselves on a national footprint. For benchmarking, national data is needed to allow comparisons due to the number of customer organisations and number of types of organisations. This would be a major improvement on the current position where the service is limited to the data flows from the local DSCRO and published data that often is not granular enough to meet user requirements. The HES data will be utilized within RAIDR to provide a range of benchmarking dashboards and reports as required to address customer specific priorities. This may include mortality, end of life, procedures of limited clinical value, new to review ratios, readmissions etc. The ability to present a national and peer-group picture of locally defined indicators is the ambition. HES data will be presented independently of existing data flows within a bespoke dashboard as well as to supplement current reports/dashboards. For example using HES to calculate a national readmission rate to be presented on a locally fed readmission report. As well as within the RAIDR tool HES data will be used by the BI team for bespoke analytics and reporting. This will include for individual commissioners who have requested a deep-dive for a particular area and want to understand how they compare to other areas. It will also help support whole provider and health economy analysis where service re-configurations are being proposed. [Note: this is not possible with the commissioner specific slices of data provisioned via the DSCRO]

Yielded Benefits:

Considerable benchmarking work across the North East to look for QIPP savings, and the ability to drill down into the datasets provided by HES to understand variation at low levels of granularity. However, even if the CSU managed to bring every CCG down to the level of the best in the North East they would still be outliers nationally, as the North East is a national outlier. To this end, HES allows the CSU to place the North East into context with other sub-regions from across the country, using identical queries, to help to explain some of the limitations of QIPP schemes, but also some of the true opportunities. Using HES NECS have undertaken national comparisons against peer groups to the levels that Right Care do not do, have undertaken further deep dive reporting into the key areas of overspend, have provided comparative analysis in their routine reporting against peer CCGs, and generally make use of best national information resource. It has facilitated their CCGs to make contact with “best in class” CCGs, identified through the interrogation of HES, who have, for example, the lowest activity rates in some of the areas we’ve been looking at. This has resulted in useful discussions with those CCGs about their activity levels. The CSU's primary use of HES this year has been to benchmark their CCGs against their peer groups as identified in the Right Care packs - https://www.england.nhs.uk/rightcare/products/nhs-rightcare-intelligence-tools-and-support/, thus giving CCGs a different perspective on potential savings against peers who they would not have been able to compare against without access to HES. The benefits of this to their CCGs is improved benchmarking to help determine where they need to focus their resource for schemes within QIPP / Financial recovery, improved monitoring, to ensure schemes put in place are actually viable, and this work has helped NECS towards becoming Kite marked by Right Care. Deep-dives have been completed for individual commissioners who want to understand how they compare to other areas to help support whole provider and health economy analysis where service reconfigurations are being proposed. NECS have utilised HES data to inform baseline capacity and demand positions for the acute sector in STPs in their footprint. In particular, one of their STPs which is well progressed, is utilising HES data to inform a capacity planning model to forecast future demand and produce scenarios for future hospital configuration. This STP includes a CCG that is outwith their traditional CCG footprint, therefore the HES data provides a consistent, baseline from which this modelling can be carried out. Working with clinicians leading the STP acute sector surgical workstream to identify the most effective configuration of acute surgery across the NTWD geographical footprint. NECS are carrying out a national project to test the effect of a range of factors on patient’s decision to attend A&E departments. In order to derive the independent variable for this model, HES was used to calculate A&E Attendance rates for each of the 5000+ GP Practices within the study.

Expected Benefits:

Utilising HES data for reporting will provide more accurate peer groups for benchmarking purposes rather than simply comparing neighboring commissioners as happens now using DSCRO supplied data. Benchmarking is currently restricted to data held by the local DSCRO so CCGs cannot be compared against their identifier peers as these are often elsewhere in the country. For example NECS recently delivered a project for NHS England to help improve the treatment of patients with dementia. National figures suggested the dementia registers in GP practices had patients missing. A dementia dashboard was developed within RAIDR to highlight to GP practices and commissioners where practices potentially had patients missing from their register based on secondary care SUS data – this was successful with the number of patients on dementia registers increasing however it could only be undertaken locally as NECS did not hold a national dataset. Another example is where the CSU (on behalf of a local CCG) has undertaken reporting of emergency admission rates with a view to altering patient pathways. Emergency admission rates for local providers have been used to identify best practice and pathways altered to reduce admissions. However this exercise was limited to local hospitals as NECS did not have national data available. The CCG were then able to compare their local pathways with others where readmission rates were lower with a view to changing how services were configured and commissioned locally. Ideally this would have allowed the CCG to compare their readmission rates with all commissioners/providers nationally but this was not possible without access to the full HES dataset. When the CSU come to extend/renew their agreement, evidence will be supplied for benefits achieved through the provision of dashboards/analysis to each type of customer organisation.

Outputs:

As described in the objectives the outputs will be two-fold: 1) Additional dashboards and reports available via the RAIDR tool to registered users covering a range of benchmarking and comparative analysis. This will include a focus on: a. Mortality b. Readmissions c. New to review ratios for outpatients d. Procedures of limited clinical value e. Falls f. Frequent flyers Allowing commissioners to compare the impact of their programmes and work streams against peer groups and nationally will help determine their effectiveness and inform future commissioning decisions. Outputs will include additions to graphs/charts showing a national and peer group figure and also tables detailing how each commissioner compares to others. The customer estimates these new dashboard will take approximately 2 months to develop and will be refreshed monthly as data is made available. 2) In addition to self-service dashboards (see above) the applicant will utilize the HES datasets to undertake various analyses both locally and in support of a range of national projects. Having the full catchment/provider data (commissioners generally only have their registered population) will facilitate accurate modelling of services and a view of complete patient pathways. Current projects where HES data would add significant value to the CSU’s services include: a. Supporting CCG vanguard applications: NECS is providing support to a number of vanguards, validating their activity/financial models and plans. Not having direct access to a standardized national dataset limits the support that can be provided. b. Service and pathway transformation: redesigning care pathways on behalf of CCGs requires access to activity data covering the entire provider with HES the only source for this. Commissioning plans must be based on accurate and complete information. The business intelligence teams within NECS would use the HES data to produce deep-dive reports and analysis on specific projects whilst ensuring small number suppression is followed for all outputs and no data is shared outside the organisation.

Processing:

1. Data will be received and stored by the data management service within NECS. This is a dedicated team responsible for the organisations data warehouses and incoming/outgoing flows of data. The HES datasets will initially land in the teams secure file share before being uploaded in to an SQL Server data warehouse. Both file share and SQL server data are securely hosted within a commercial grade data centre. 2. The data management service will create derived fields based on the data received such as Ambulatory care sensitive condition flag, procedure of limited clinical value flag etc. 3. Data will be used to populate secure data cubes for use by analysts within the CSU. The data being made available will be record level but no identifiable data will be included. Only the minimum required data fields will be used to populate each cube. 4. Data will be used by the RAIDR support team to populate the relevant dashboards and reports within the RAIDR system. No patient level data will be available to RAIDR users. Small number suppression rules will be adhered to. 5. Record level HES data will not be directly linked to any other dataset. Staff follow strict rules on accessing, analysing and processing data. Only aggregate data will leave the CSU. All small numbers will be suppressed before any data is made visible to customers outside of the organisation. Small numbers will be suppressed in line with the HES analysis guide. Pseudonymised, rather than anonymised, data is required to enable calculation of benchmarked metrics on a per patient basis e.g. average number of A&E attendances per patient. For clarity, this request is for non-identifiable, pseudonymised data to flow into the data management team of North of England Commissioning Support Unit.