NHS Digital Data Release Register - reformatted
NHS North And East London Commissioning Support Unit projects
277 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
HES data for all CSUs and NHS England NIC-371243-H1P5T-2019/20 — DARS-NIC-371243-H1P5T
Type of data: Pseudonymised
Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data, Flow to de-identified environment - no analysis on confidential patient information)
Legal basis: Health and Social Care Act 2012, Health and Social Care Act 2012 – s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 s261(1) and s261(2)(b)(ii), Health and Social Care Act 2012 - s261 - 'Other dissemination of information', Health and Social Care Act 2012 s261(2)(b)(ii), NHS England De-Identified Data Analytics and Publication Directions 2023
Purposes: Yes, Commissioning Support Units (CSUs) are part of NHS England (NHS E), and provide comprehensive business intelligence (BI) services to a wide range of NHS organisations, this includes both standard analytics and reporting, deep-dives and diagnostic exercises to offer insight and intelligence on a commissioners health economy. In addition, CSUs offer business intelligence applications allowing self-service access to a range of dashboards and configurable reports. Tools are available on a subscription-basis only to NHS organisations, limited to Clinical Commissioning Groups (CCGs), internally within the CSUs through specialist support teams, by CCG member practices, and by local authorities. The Commissioning Support Units providing the services are: - North East London Commissioning Support Unit - North of England Commissioning Support Unit - South, Central and West Commissioning Support Unit - Midlands and Lancashire Commissioning Support Unit - Arden and Greater East Midlands Commissioning Support Unit NHS Englands lawful basis for processing is 6(1)(e) exercise of official authority . For special categories (health) data the basis is 9(2)(h) health or social care . NHS England (as the legal entity) is the sole data controller, and the CSUs (as part of NHS England) are data processors. Microsoft Azure provides cloud storage services for all commissioning support units and is therefore 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. ANS Group Ltd are assisting South Central and West CSU to transition to CLOUD services and are therefore a data processor. ANS Group will be supplying support, platform build and management services for SCW CSUs Cloud environment. As such, they could have access to pseudonymised / aggregate / anonymous data through system administration accounts. Whilst ANS Group are a data processor as they will have sight of the data, they will not process the data for any other purpose than IT support. ANS Group using the data for any other purpose would be considered a breach of this agreement. Hospital Episode Statistics (HES)and Emergency Care Data Set (ECDS) are required to provide support to CCGs, other commissioning bodies, and local authorities working with CSUs to meet their statutory duties under the Health & Social Care Act 2012 and to support NHS health economy wide transformation projects. The full, national set of HES and ECDS data allows complex and detailed modelling and benchmarking of activity and diagnostic interventions (numbers and rates), essential to successful commissioning of services and contract monitoring, including analysing relationships and influences between A&E, Inpatient and outpatient care and use of diagnostic services. This will especially support benchmarking work for CCGs, other commissioning clients and local authorities taking part in health economy wide transformation projects that require detailed and comprehensive hospital level data. There will be no direct linkage between HES data records and other data already used by any CSU or in the BI tools. 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. CCGs only receive local/regional commissioning flows of data such as SUS and local flows filtered by resident/registered populations, so analysis undertaken on national data such as HES provides significant added value. These data sources will allow CCGs, other commissioning organisations and local authorities to benchmark and highlight areas of variation, so that best practice can be identified in similar health economies anywhere in England. The data purpose relates to the need for national data for comparative analysis, benchmarking and forecasting, and this requirement for CSUs has specified support from NHS England. Having an extended time trend also provides valuable longer-term context when looking at health populations (e.g. health needs analysis, health economics) and service transformation. National data covering a number of years is required for benchmarking purposes, enabling users to compare themselves on a national footprint. CSUs therefore require HES data with a 10-year rolling history to enable them to provide accurate time-series forecasting methodologies. Forecasting, particularly with regards to winter surge management or financial planning, are key areas of interest for the NHS currently and are areas that the NHS North of England CSU (NECS) have used the HES data to support most recently. As the NHS evolves, there is a greater emphasis on CCGs forming part of larger collaborations called Sustainability and Transformation Partnerships (STPs), and CSUs need to accelerate this way of working throughout the country, through partnerships of care providers and commissioners in an area STPs. Some areas are now ready to go further and more fully integrate their services and funding, and CSUs will back them in doing so (Integrated Care Systems). Provision of modelling support to emergent Integrated Care Systems (ICSs) thus supporting the whole health system through modelling demand and capacity primarily in secondary care. To support the on-going budgetary pressures the NHS is faced with, the BI services and CSU BI tools offer significant support to commissioners on their Quality, Innovation, Productivity and Prevention (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. Working together with patients and the public, NHS commissioners and providers, as well as local authorities and other providers of health and care services, ICSs will plan how best to provide care, while taking on new responsibilities for improving the health and wellbeing of the population they cover. Under this agreement, the CSUs will use the data provided for 2 purposes: i) benchmarking dashboards and reports, and ii) bespoke analytics and reporting. The HES data will be utilised within CSU BI tools to provide a range of benchmarking dashboards and reports as required to address specific priorities. This may include mortality, end of life, procedures of limited clinical value, new to follow-up 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 BI tool, HES data will be used by the BI team for bespoke analytics and reporting. This will include analysis on behalf of individual CCGs 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. (Commissioning Support Unit (CSU), internal NHS transfer)
Sensitive: Non Sensitive, and Non-Sensitive
When:DSA runs 2019-09-03 — 2020-09-02 2017.06 — 2023.08.
Access method: Ongoing, Frequent Adhoc Flow
Data-controller type: NHS ENGLAND (QUARRY HOUSE)
Sublicensing allowed: No, Yes
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Accident and Emergency
- Hospital Episode Statistics Critical Care
- Hospital Episode Statistics Outpatients
- Diagnostic Imaging Dataset
- Bridge file: Hospital Episode Statistics to Diagnostic Imaging Dataset
- Emergency Care Data Set (ECDS)
- HES-ID to MPS-ID HES Accident and Emergency
- HES-ID to MPS-ID HES Admitted Patient Care
- HES-ID to MPS-ID HES Outpatients
- Diagnostic Imaging Data Set (DID)
- Hospital Episode Statistics Accident and Emergency (HES A and E)
- Hospital Episode Statistics Admitted Patient Care (HES APC)
- Hospital Episode Statistics Critical Care (HES Critical Care)
- Hospital Episode Statistics Outpatients (HES OP)
The HES data will only be used by North and East London Commissioning Support Unit (NELCSU) to provide support to Clinical Commissioning Groups (CCGs) and other commissioning bodies working with NELCSU to meet their statutory duties under the Health & Social Care Act 2012 and NHS health economy wide transformation projects that require detailed hospital level data.
The pseudonymised record level HES data is interrogated only by approved NELCSU substantively employed analysts to provide benchmarking and comparative information to NELCSU clients and NHS health economy wide transformation projects that require detailed hospital level data.
The full, national set of HES data allows complex and detailed modelling and benchmarking of activity, essential to successful commissioning of services and contract monitoring, including analysing relationships and influences between A&E, Inpatient and outpatient care. This will especially support benchmarking work for CCG clients taking part in health economy wide transformation projects that require detailed and comprehensive hospital level data (for example from local SUS data feeds the applicant only receives data for their CCG’s registered population, which does not allow whole trust activity to be considered) and allow CCGs to benchmark and identify best practice in similar health economies anywhere in England.
All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide.
Some of the yielded benefits of HES data to date are: 1) Assisting NHS England in London, at identifying the rates of GP referrals to hospitals across all the CCGs in London. There is a lot of variation, both between CCGs and between GP Practices within a CCG area and NELCSU have compared these in a way that accounts for these areas very different populations (in statistical terms this is known as “standardisation”. The NHS is experiencing significant pressure and unprecedented levels of demand. The average annual growth in GP referrals between 2009/10 and 2014/15 was 3.9%. Growth in 2015/16 compared to 2014/15 was 5.4%. For the same period, other referrals, which include consultant to consultant referrals grew by 6.7%. There is clearly a significant need for the NHS to manage the demand that flows into hospitals by ensuring that only the most appropriate cases are referred for face to face consultation. There is also evidence to suggest that a referral to hospital is not always necessary. NHS England have published a demand management “Good Practice Guide” covering areas such as “peer review of referrals”, “shared decision making” and “advice and guidance”. The results of this analysis help identify which geographies to target, inform the conversation around appropriate areas to change and help monitor the impact of any implemented demand management schemes. 2) Assisting a CCG in the South of England implement improvements in the area of diabetes and respiratory disease. The improvements will involve the health system – GPs, hospitals, community services – working more effectively together (or in the jargon working in a more “integrated” way). HES data has been used to identify variation in “outcomes” to identify potential areas to target. For example HES data was used to identify the numbers of patients admitted with complications of diabetes, as these are an indicator that a patient’s condition has deteriorated, something that could possibly be counteracted with better management of a patient’s condition within primary care. Are these numbers high relative to other areas? How much do they vary by GP practice? What is the real reason behind this variation? Integrated care schemes internationally have evidenced significant benefits in improving patient outcomes, experience of care and reducing costs to the health system. This project is the first stage of a pilot, and will be extended out to a wider geography and to other clinical areas. 3) Identifying potential influences on high A&E attendance rates. Within London, most A&E departments are under huge pressure from rising A&E demand. However, the rate of increase does vary significantly by geography and by patient group. By using national HES data NHS North and East London Commissioning Support Unit were able to undertake statistical modelling of most of the known drivers of A&E attendance and try to understand the relative importance of each. For example, patient ethnicity appears to be one influence. Those ethnic groups with high attendance rates can be targeted through communication campaigns or through their GPs to encourage use of alternative services where possible. The better that the reasons for growing A&E demand can be understood, the more effective commissioners can be in tackling the root cause of the issue.
CCGs and Local Authorities (Public Health teams) have joint statutory duties under the Health and Social Care Act 2012 to plan and commission services and jointly assess the needs of their patients and populations, to ensure that health improvements and better outcomes are measurable, identifiable and attainable.
Analysis of HES and DIDs data helps these organisations achieve this by providing the greatest scope to evaluate outcomes of care and improvement in their health services against peer groups and national achievement – providing a more extensive and complete base of knowledge for decision making than data on their own patients alone (SUS data).
Measurable benefits can occur, for example, through gradual improvement in outcome over a number of years, to more immediate commissioning new services where a gap is identified, or de-commissioning failing services by identifying lower outcomes than is acceptable, compared to the norm.
Examples of benefits achieved to date include:
a. NELCSU supported a major reconfiguration of cancer and cardiac services in North London. The detailed numbers to support the case for change were extracted from the raw HES data. This was a complex exercise, requiring clinical input to define the primary and secondary coding of the patient cohorts affected by the change. This would only be possible through using very granular data which covers whole hospital activity (rather than for our customer CCGs). The rigour of the work helped with forming realistic planning assumptions and obtaining clinical and provider buy in for changes.
b. NELCSU are currently supporting NHS England with work identifying the highest and lowest referrers within London by CCG and by GP Practices within each CCG. This work requires whole London data and as it adopts age and sex standardisation needs data to a very granular level. We have also applied certain filters that improve the accuracy of the benchmarking from detailed analysis of the data. This project is currently supporting NHS England in a London-wide demand management programme which aims to ease the pressure on acute hospitals by targeting those CCGs and practices with abnormally referral rates.
Outputs are on an on going basis (i.e., no target date) as the HES data in general is used to support general commissioning and public health needs, and is not aimed at a specific report or deadline for use.
All outputs informed by information retrieved from the HES data tables are governed by adherence to the HES guidance on suppression of small numbers. Users of the data abide by the HES Analysis Guide which means that all outputs released must be aggregated with small numbers suppressed.
HES allows NELCSU to provide intelligence for programmes whose scope demands activity benchmarking of the CSU's clients (CCGs) against similar health economies or populations in England. SUS data does not allow this scope. National data also supports NHS health economy wide transformation projects that require detailed and comprehensive hospital level data.
Commissioners can compare with any service known to have better outcomes or new pathways, or support large scale transformation projects that may impact several commissioners across, for example, the North London area.
Outputs expected are aggregated data to support reports or decisions across examples such as the following:
• Elements of Joint Strategic Needs Assessments (JSNA) - to support CCGs/Local Authorities to consider the needs of their local populations and in how they respond with effective commissioning of services to properly meet those needs, by enabling, for example views of the use of secondary services by different patient groups by condition, ethnicity, etc.
• Quality, Innovation, Productivity and Prevention (QIPP) development - identifying and benchmarking areas across England with better practice than locally, to help evaluate high costs and poor outcomes in hospital care.
• Providing data on hospital admissions in-year to support monitoring of national ambitions, such as avoiding unnecessary admissions across CCGs, by practice, condition, hospital trust. CCGs are required to monitor and make progress on national outcome measures and ambitions by NHS England, and use of national benchmarking is promoted heavily by initiatives such as Right Care ‘Commissioning for Value’ (on behalf of NHSE). Without access to national data such as HES, CCGs cannot be ultimately certain that they are making progress or making decisions on the best basis possible.
Diagnostic Imaging is an acknowledged area of over/ duplicate treatment and so a fruitful area for NELCSU to investigate and to support improvement initiatives (eg Right Care). The DIDs data with linkage to HES will help with any deep dives and provide further opportunities for gaining insight from this data. As an example some of NELCSU customer CCGs have very high diagnostic intervention rates per head of population (eg for MRIs). Having DIDs data allows NELCSU to have the detailed data to be able to investigate these type of issues in more detail and provide useful outputs.
Only an approved list of NELCSU substantively employed analysts have access to the full set of pseudonymised data tables, via secure server based Structured Query Language (SQL) querying. The data will only be for the purposes described in this document and not for any other purposes, including being used in data tools.
CSU analysts interrogate the data to produce aggregated output for monitoring care outcome and activity for a CCG’s population, patient group, condition or service provider, including trends over time in any given activity or care process. For example, trends over time can be modelled to produce forecasts of future activity, taking into account population growth or changes in service configuration.
National data is necessary to benchmark against any CCG peer groups (as defined by NHS England), or any other care pathway or group of patients. Benchmarking allows an individual CCG to evaluate its own care processes and outcomes against other similar commissioning populations, with a view to identifying areas for improvement or to identify best practice. National data also supports NHS health economy wide transformation projects or other commissioning initiatives that require detailed and comprehensive hospital level data.
Analysts will only release aggregated data with small numbers suppressed in line with the HES Analysis Guide.
The data is being held within a data centre which also holds data on behalf of other organisations. The applicant agrees that the data under this agreement must be held and remain separate to all other data (except where explicitly stated within the agreement), and accepts full responsibility for the breach of this agreement should this not be the case. In order to mitigate this risk, it is strongly recommended that the applicant considers the best practice controls as detailed in ISO 27017:2015 Code of practice for information security controls based on ISO/IEC 27002 and ISO 27018:2014, which establish commonly accepted control objectives, controls and guidelines for implementing measures to protect Personally Identifiable Data.
For clarity, any access by Interxion 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.