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
Opt outs honoured: No - data flow is not identifiable, Anonymised - ICO Code Compliant, No (Does not include the flow of confidential data)
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)
Purposes: Yes (Commissioning Support Unit (CSU))
Sensitive: Non Sensitive, and Non-Sensitive
When:DSA runs 2019-09-03 — 2020-09-02 2017.06 — 2022.12.
Access method: Ongoing, Frequent Adhoc Flow
Data-controller type: NHS ENGLAND (QUARRY HOUSE)
Sublicensing allowed: No
Datasets:
- 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)
Objectives:
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.
Yielded Benefits:
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.
Expected Benefits:
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:
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.
Processing:
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.