NHS Digital Data Release Register - reformatted
The Royal Wolverhampton NHS Trust projects
- Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System (partially via "system access")
- Request for HES mortality data link to NNRD for NIHR -HS & DR funded project Opti-Prem
84 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).
Cancer Alliance access to National Cancer Waiting Times Monitoring Data Set (NCWTMDS) from the Cancer Wait Times (CWT) System — NIC-795868-X8R6B
Opt outs honoured: unknown (Excuses: Does not include the flow of confidential data)
Legal basis: Health and Social Care Act 2012 s261(2)(a)
Purposes: No (NHS Trust)
Sensitive: Non-Sensitive
When:DSA runs 2026-02 – 2029-02 2026.04 — 2026.04.
Access method: System Access
(System access exclusively means data was not disseminated, but was accessed under supervision on NHS Digital's systems)
Data-controller type: THE ROYAL WOLVERHAMPTON NHS TRUST
Sublicensing allowed: No
AGD/predecessor discussions: List of projects wihtout minutes
Datasets:
- National Cancer Waiting Times Monitoring DataSet (NCWTMDS)
Type of data: Anonymised - ICO Code Compliant (note: this information not disclosed for TRE projects )
Objectives:
Improvements for Cancer patients:
In 2015, the independent Cancer Taskforce set out an ambitious vision for improving services, care and outcomes for everyone with Cancer: fewer people getting Cancer, more people surviving Cancer, more people having a good experience of their treatment and care, whoever they are and wherever they live, and more people being supported to live as well as possible after treatment has finished. In 2019, the NHS Long Term Plan was published and it aims to improve how we diagnose and treat cancer. The plan included cancer care as one of its clinical priorities and aimed to boost cancer survival rates by focusing on early diagnosis. The plan set new targets that, by 2028, the proportion of cancers diagnosed at stages 1 and 2 will rise to 75% of cancer patients. Further, an extra 55,000 people each year will survive for 5 years or more following their cancer diagnosis.
Cancer Alliances:
Cancer Alliances have a crucial role to play by being the cancer arms of their ICSs and being the leaders for cancer within their ICB and ICS footprint. Their role is to lead the planning and delivery of the Long-Term Plan ambitions for cancer for their populations, to provide system oversight and co-ordination for cancer services and to oversee the delivery of critical programmes of work within that footprint. They do this by:
Collaborating with partners (ICSs, commissioners and providers) to provide system level oversight and co-ordination to deliver the operational standards for cancer and the Long Term plan ambitions across their cancer system;
Deploying service development funding in a way that supports their whole population, and which complements baseline investment so that it maximises the impact on improving cancer outcomes;
Providing clinical leadership for cancer services across their area to ensure the delivery of a consistently high level of service to patients and to drive the rapid adoption of new approaches; and
Working as part of the NHS Cancer Programme to share best practice and solutions, and to provide peer support to other Alliance teams.
Cancer Alliance boundaries encompass the range of providers that a cancer patient will typically use. This gives them an opportunity to organise services across organisation boundaries reducing variation and inequalities, and overall benefitting patients
Cancer Wait Times (CWT) system:
The Cancer Wait Times (CWT) system collects and validates the National Cancer Waiting Times Monitoring Data Set (NCWTMDS), allowing performance to be measured against operational Cancer standards. Data is validated and records merged to the same pathway to cover the period from referral to first definitive treatment for Cancer and any additional subsequent treatments.
The CWT system then determines whether the operational standard(s) that apply were met or not for the patient and the accountable provider(s). The CWT system holds NCWTMDS in a series of pre-aggregated static reports. These reports are available monthly and quarterly data (aligned with the National Statistics for Cancer Waiting Times published by NHS England). Users can query the CWT system to generate reports to feedback on the progress towards meeting these targets.
The Royal Wolverhampton NHS Trust and Nottingham University Hospitals NHS Trust will directly access the Cancer Waiting Times System on behalf of West Midlands Cancer Alliance across the West Midlands. West Midlands Cancer Alliance is hosted by The Royal Wolverhampton NHS Trust and covers a population of 6.5 million people.
The West Midlands Cancer Alliance hosted by The Royal Wolverhampton NHS Trust employs staff from Nottingham University Hospitals NHS Trust and works with health organisations across the West Midlands including 15 acute providers and 6 ICBs.
Acute Providers:
Birmingham Women's and Children's NHS Foundation Trust
George Eliot Hospital NHS Trust
Sandwell And West Birmingham Hospitals NHS Trust
South Warwickshire University NHS Foundation Trust
The Dudley Group NHS Foundation Trust
The Robert Jones and Agnes Hunt Orthopaedic Hospital NHS Foundation Trust
The Royal Orthopaedic Hospital NHS Foundation Trust
The Royal Wolverhampton NHS Trust
The Shrewsbury and Telford Hospital NHS Trust
University Hospitals Birmingham NHS Foundation Trust
University Hospitals Coventry and Warwickshire NHS Trust
University Hospitals of North Midlands NHS Trust
Walsall Healthcare NHS Trust
Worcestershire Acute Hospitals NHS Trust
Wye Valley NHS Trust
ICBs:
Birmingham and Solihull ICB
Black Country ICB
Coventry and Warwickshire ICB
Herefordshire and Worcestershire ICB
Shropshire, Telford and Wrekin
Staffordshire and Stoke on Trent
Data access:
The CWT system provides one organisation (the lead organisation) representing each Cancer Alliance, with access to the following:
a) Aggregate reports (which may include unsuppressed small numbers)
b) Pseudonymised record level data - users can directly download this data from the CWT system
c) I-View Plus tool
Lead organisations will only access patient records which fall within the Cancer Alliances' footprint of responsibility based on the patients' ICB of responsibility. This Cancer Alliance is limited to West Midlands Cancer Patients. CCGs no longer exist in statute, but NHS England use the CCG field as the geographical variable to split the CWT extracts that are sent to Cancer Alliances.
A) Aggregate reports including small numbers
Aggregate data is available in the form of reports at Provider (Trust) and Integrated Care Board (ICB) level.
Small numbers may be included in the aggregate data reports and are essential for analyses carried out by lead organisations.
Investigating breaches
Lead organisations routinely monitor performance and standards using the CWT system, particularly in relation to breaches of the 62 day wait target. Due to the large number of potential Trust/ICB combinations, breach counts could result in small numbers as in some cases there are less than 6 breaches in a whole year. Given that financial penalties are linked to target breaches counts must accurately reflect the true percentage without suppression.
Mitigating risk of re-identification
Risk of disclosure is minimised as the dataset does not include patient demographics (increasing risk of re-identification) that may allow users to identify an individual e.g. there are no age, ethnic categories or geographic breakdowns based on patient postcode.
Additionally, the aggregation categories are such that the data is not at a lesser granular level e.g. the source NCWTMDS data collects information at ICD diagnosis code level, but the CWT system aggregates at tumour group level e.g. Head & Neck, Upper GI, lower GI, Breast etc.
B) Pseudonymised record level extracts
Lead organisations will access record level pseudonymised data which includes the system generated pseudo CWT patient ID.
Any record level data extracted from the system will not be processed outside of the authorised users of the system.
C) i-View Plus .
iView Plus uses cube functionality to allow lead organisations to produce graphs, charts and tabulations from the data through the construction of queries. The data in iView plus is split by operational standard being measured and can then be analysed against a range of dimensions collected in the data and measures such as count, percentage and median. The outputs of iView Plus are aggregate, and no record level data can be obtained, however some queries may result in small numbers and these currently have limited disclosure control applied, see A) for further explanation.
iView Plus holds published data, the lowest organisational granularity is trust level, data can also be aggregated to ICB level and other health hierarchies.
Lead organisations will use the data to both monitor and improve performance against the Cancer Waiting Time standards and to inform wider Cancer pathway improvements.
Lead organisations use of the data will fall into two separate categories, each requiring different levels of suppression, and onward sharing both within the Cancer Alliance and with wider NHS stakeholders;
Purpose One - Aggregate local reports
Generation of routine Cancer Waiting Times reports at Provider (Trust) or ICB level. Lead organisations will access a summary of the totals for the Providers (Trust) and ICB's that are treating cancer patients where they have a commissioning responsibility for that patient (based on the ICB they are aligned to). This analysis would then be shared with the providers and commissioners and used to inform service improvement by providing benchmarked comparable data. The format of this report would be in a tabulated or graphical form (i.e. not record level) but may contain small numbers. An example of where small numbers would not be suppressed would be in relation to cases of breaches against a standard where small numbers would be essential to ensure the report is meaningful.
Examples of this type of analysis include:
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and ICBs across the geography
b. Analysis of Cancer Waiting Times performance by treatment modality
c. Grouping length of waits for standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Reviewing waits between surgery and radiotherapy for Head and Neck Cancer patients with a maximum recommended wait of 6 weeks
h. Reviewing routes to diagnosis of patients
i. Quantifying treatment volumes by provider organisation including analysis treatment rates
Purpose Two - Sharing of record level data (including free text breach reasons) with providers and commissioners responsible for direct patient care for that patient. This will be for local audit purposes.
The two broad purposes for this would be;
1) To support audit work
2) Investigate individual outliers to the national standards
Pathway analysis will be undertaken, identifying trends in reasons for breaches. The analysis will inform system wide pathway improvements and compliance to the national standards. Examples of potential changes to achieve this could be to support trusts in additional resources and processes and also to facilitate discuss between trusts for example in reaching agreement for diagnostics between trusts.
Examples of the types of reasons for this include;
a. Patients waiting excessively long period of time to seen of received treatment
b. Free text breach reasons identifying areas of concern which require more detail or clarification from provider
c. Identification of 28 day standard exceptions - National guidance states patients who are diagnosed with cancer should be informed face to face, this would highlights numbers of patients who are not told in person by provider
d. Audits to review orphan records which require local providers to review local patients records
Record level data (pseudonymised) will be shared via NHS.UK email accounts and access will be controlled by password protecting all files.
Yielded Benefits:
Cancer Alliances have previously had access to Cancer Waiting Times reports and pseudonymised data through the system on Open Exeter, under an agreement with NHS England. This has enabled analysis to inform service improvement both to achieve the national Cancer Waiting Times standards and also wider Cancer pathway improvement work, which will have contributed to oncoming improvements to Cancer survival, and patient experience.
Expected Benefits:
1) Benefits type: Supporting delivery of CWT standards
The Cancer Waiting Times standards are key operational standards for the NHS, which aim to reduce the waits for diagnosis and treatment for Cancer patients, which will support improvements to survival rates and improve patient experience. These include the 3 combined operational standards which came into existence in October 2023 (28 day Faster Diagnosis, 31 day Treatment and 62 day Standards).
A key enabler to achieve these standards, and thus improve survival and patient experience is the role of Cancer Alliances locally to work with providers and commissioners to improve patient pathways. Access to the Cancer Waiting Times data as detailed in the above will enable Cancer Alliances to have informed discussions and allocate resources optimally to improve performance against these standards. It will also enable Cancer Alliances to work with local providers and commissioners to identify outliers against the standards and mitigate the risk of similar delays for other patients.
Improvement would be expected on an on-going basis with the combined standards, based on the previous nine standards, being in place since October 2023:
8-day Faster Diagnosis Standard (75%)
31-day decision to treat to treatment standard (96%)
62-day referral to treatment standard (85%)
2) Benefits type: Improvements beyond constitutional standards
This access and resulting analysis will enable Cancer Alliances to undertake local analysis beyond the Cancer Waiting times operational standards to support improvements to Cancer patients pathways beyond those already achieved by improving performance against standard set. This could include reviewing times between treatments, or treatment rates.
The overall aim of this type of additional analysis would be to support improvements to Cancer patients survival and experience. The NHS Long-Term plan built on the previous Cancer Taskforce recommendations relating to survival and early diagnosis, and has set out ambitions to improve early diagnosis (patients stage 1 or 2) to 75% (subject to review and change at the time of writing) and that an extra 55,000 people each year will survive for 5 years or more following their cancer diagnosis by 2028. For both of these improvements to the diagnostic and treatment pathways are key and require Cancer Alliances to be able to analyse the Cancer Waiting Times dataset to identify sub-optimum pathways and resulting improvements.
Outputs:
Outputs fall into the following categories:
1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and ICBs.
b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions
c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays.
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Outlier identification including exceptionally long waits to inform individual queries to providers
2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patients' outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust.
The overarching aim of all future analysis/outputs is to inform priorities and potential investment to improve Cancer pathways including reducing Cancer incidence and mortality, improving Cancer survival, improving patient experience, improving service efficiency and meeting national constitution standards relating to Cancer patients'.
Processing:
Access to the Cancer Wait Times (CWT) System will enable Cancer Alliances to undertake a wide range of locally-determined and locally-specific analyses to support the Long-Term Plan ambitions for early diagnosis and survival and the previous Cancer Taskforce vision for improving services, care and outcomes for everyone with Cancer.
The Royal Wolverhampton NHS Trust and Nottingham University Hospitals NHS Trust will directly access the Cancer Waiting Times system. Extracts can be downloaded and will be stored on the The Royal Wolverhampton NHS Trust and Nottingham University Hospitals NHS Trust's servers and NHS Sharepoint (Microsoft Corporation Limited). Role Based Access Control prevents access to data downloads to employees outside of the West Midlands Cancer Alliance analytical team responsible for producing outputs.
The CWT system is hosted by NHS England, access to and usage of the system is fully auditable. Users must comply with the use of the data as specified in this agreement. The CWT system complies with the requirements of NHS England Code of Practice on Confidential Information, the Caldicott Principles and other relevant statutory requirements and guidance to protect confidentiality.
Access to the CWT system will be granted to individual users only when there is a valid Data Sharing Agreement between the lead organisation and NHS England.
Approved users will log into the system via an N3 connection and will use a Single Sign-On (users are prompted to create a unique username and password).
The Royal Wolverhampton NHS Trust and Nottingham University Hospitals NHS Trust users will access:
a) Aggregate reports (which may include unsuppressed small numbers)
b) Pseudonymised record level data - users can directly download this data from the CWT system
c) I-View Plus tool (aggregated - access to produce graphs, charts/tabulations from the data through the construction of queries). This will give users access to run bespoke analysis on pre-defined measures and dimensions. It delivers the same data that is available through the reports and record level downloads (i.e. it will not contain patient identifiable data).
Any record level data extracted from the system will not be processed outside of the The Royal Wolverhampton NHS Trust and Nottingham University Hospitals NHS Trust unless otherwise specified in this agreement. Following completion of the analysis the record level data will be securely destroyed.
Users are not permitted to upload data into the system.
Data will only be available for the Providers (Trust) and ICBs that are treating cancer patients where they have a commissioning responsibility for that patient (based on the ICB that this Cancer Alliance is aligned to).
The data will only be shared with other members of the Cancer Alliance in the format described in purpose 1 and purpose 2 of this agreement. The primary method for sharing outputs is via Email.
Aggregate data/ graphical outputs may be shared via e-mail; for example as part of Alliance meeting papers.
Where record level data is shared with individual trusts these are shared only with trust(s) who were involved in the direct care of the patient, only via NHS.net email accounts.
As part of partnership working to improve Cancer Waiting Times performance, aggregated and supressed outputs may be shared with national/ regional bodies including the Midlands regional team. Data will only be shared as described in purpose one and purpose two of this agreement.
Training on the CWT system is not required as it is a data delivery system and it does not provide functionality to conduct bespoke detailed analysis. User guides are available for further assistance.
Access to the CWT system data is restricted to Cancer Alliance employees who are substantively employed by The Royal Wolverhampton NHS Trust and Nottingham University Hospitals NHS Trust in fulfilment of their public health function.
The Cancer Alliances will use the data to produce a range of quantitative measures (counts, crude and standardised rates and
ratios) that will form the basis for a range of statistical analyses of the fields contained in the supplied data.
Typical uses will include:
1) Analysis to support delivery of Cancer Waiting Times standard and identify variation, including clinical discussions to improve patient pathways
a. Comparative Cancer Waiting Times performance at tumour group and individual tumour site (i.e. ICD10 code) level for Trusts and ICBs.
b. Analysis of Cancer Waiting Times performance by treatment modality to inform discussions
c. Grouping length of waits for standards to inform discussions on going beyond constitutional standards
d. Analysis of free text and derived breach reason fields to identify trends in reasons for delays.
e. To provide assurance through comparative analysis (e.g. orphan record identification, active monitoring proportions and validation of waiting list adjustments entered)
f. Analysis of flows of patients including analysis by provider trust site
g. Outlier identification including exceptionally long waits to inform individual queries to providers
2) Cancer Waits analysis (not directly linked to constitutional standards) for the aim of identifying variation which may impact Cancer patients' outcomes or patient experience. Examples for use of the data may include reviewing waits between surgery and radiotherapy for Head and Neck cancer patients' with a maximum recommended wait of 6 weeks and using the data source to validate surgical numbers by provider trust.
Request for HES mortality data link to NNRD for NIHR -HS & DR funded project Opti-Prem — NIC-125031-Z3D7S
Opt outs honoured: Yes - patient objections upheld, Yes (Excuses: Section 251 NHS Act 2006, Does not include the flow of confidential data)
Legal basis: National Health Service Act 2006 - s251 - 'Control of patient information'. , Health and Social Care Act 2012 - s261 - 'Other dissemination of information'; National Health Service Act 2006 - s251 - 'Control of patient information'., Health and Social Care Act 2012 s261(2)(a); National Health Service Act 2006 - s251 - 'Control of patient information'.
Purposes: No (NHS Trust)
Sensitive: Sensitive, and Non Sensitive, and Non-Sensitive
When:DSA runs 2020-12 – 2023-12 2021.03 — 2022.08.
Access method: One-Off
Data-controller type: THE ROYAL WOLVERHAMPTON NHS TRUST
Sublicensing allowed: No
AGD/predecessor discussions: AGD minutes - 18 April 2024 final.pdf, igarddraftminutes10thdecember2020final.pdf
Datasets:
- Civil Registration - Deaths
- HES:Civil Registration (Deaths) bridge
- Hospital Episode Statistics Admitted Patient Care
- Hospital Episode Statistics Outpatients
- Hospital Episode Statistics Critical Care
- Civil Registration (Deaths) - Secondary Care Cut
- Civil Registrations of Death - Secondary Care Cut
- Hospital Episode Statistics Admitted Patient Care (HES APC)
- Hospital Episode Statistics Critical Care (HES Critical Care)
- Hospital Episode Statistics Outpatients (HES OP)
Type of data: Anonymised - ICO Code Compliant
Objectives:
BACKGROUND
The Neonatal Data Analysis Unit (NDAU) is a section within Imperial College's Chelsea and Westminster hospital campus. The NDAU receives pseudonymised neonatal data for the whole of England from CleverMed, who are the creators of the electronic medical records system that stores this data. From this received data, NDAU creates the National Neonatal Research database (NNRD), which essentially holds hospital admissions data for new-born babies in the UK. All employees at NDAU are substantiate Imperial College staff. More details about NDAU and NNRD at https://www.imperial.ac.uk/neonatal-data-analysis-unit.
The Optimising neonatal service provision for preterm babies born between 27 and 31 weeks of gestation in England, using national data, qualitative research and economic analysis (OptiPREM) study, is one that seeks to establish best place of care for babies born between 27-31 weeks of gestation. The study data comes from an extraction of the NNRD on this specific age group for those born in England. As part of the work for the OptiPREM study, additional data is required on babies born between 27 – 31 weeks in England, beyond what is captured by the NNRD (NNRD only captures information on babies while they are admitted in the neonatal unit).
The cohort is all babies born with a gestational age between 27+0 weeks and 31+6 weeks at birth,and discharged between the time periods 01 January 2014 to 31 December 2018 in England.
This extra information required for the project involves an assessment of hospital care, for up to two years of age. This includes hospital care after the baby has been discharged from neonatal care i.e. readmitted or reviewed in a hospital setting after being discharged from the neonatal unit.
This hospital care for babies after discharge from neonatal care is captured by NHS Digital HES/Mortality, and is the reason for this NHS Digital application
The project aims to improve health outcomes overall – the likely full impact of this project can be seen in section 5d below. These include impact on babies, mothers, families, clinical teams, health care providers service provision and commissioning. NHS Digital data will be used in a part of the OptiPrem project (Workstream 3). This workstream evaluates the cost of care for all preterm babies born between 27-31 weeks in England, up to the time they reach two years of age. It will look to see whether it is cost effective to be born and looked after in one of two types of neonatal units: a neonatal intensive care unit (NICU) or a local neonatal unit (LNU). It will see assess whether this influences the longer-term cost of medical care up to two years of age). The dataset for this project is called The OptiPrem dataset and comes from the NNRD.
It is important to note that the economic cost of care forms just one stream of the entire project. The project evaluates best place of care based on key clinical outcomes i.e mortality and major morbidity. These are being undertaken in different workstreams that do not require NHS digital linkage and are not part of this application. In the event that there is no difference in place of care, based on the key clinical outcomes, then the economic cost of care will be used to define recommendations nationally, together with parent staff perceptions (separate workstream).
The NNRD only captures neonatal admission data (this usually lasts a few weeks for babies born in this age group 27-31 weeks). This project looks at outcomes (hospital admissions, critical care, out-patient visits, and deaths up to two years of age) and works out the costs associated with this care. The OptiPREM study team at University of Oxford need NHS Digital data because it has data that covers the two-year time point that is needed; this is not available via the NNRD.
The OptiPREM study team at University of Oxford will use the NNRD data to calculate costs of care while the baby is an inpatient on the neonatal unit (captured on NNRD and not on NHS digital), and the NHS Digital HES and mortality data will be used to calculate the cost of care after the baby is discharged from the neonatal unit up to time of death or two years of age (this is captured on NHS digital HES/Mortality).
The OptiPREM team will be utilising the data from NHS Digital (HES and mortality), linked to the OptiPrem cohort babies (27-31 weeks gestation) in the OptiPrem dataset.
The cohort is all babies born with a gestational age between 27+0 weeks and 31+6 weeks at birth,and discharged between the time periods 01 January 2014 to 31 December 2018 in England.
The OptiPREM team based at University of Oxford will calculate the cost of care for babies born at each gestational age (i.e. 27, 28, 29, 30, 31 weeks) and for each type of unit (i.e. Local Neonatal Unit vs Neonatal Intensive Care Unit) while they are in hospital in a neonatal unit (i.e. the first few weeks of life), using NNRD data, and then after they are discharged from the neonatal unit, and are seen at hospital/outpatient clinic/critical care/ etc up to time of death or two years of age, whichever comes first. For the latter data from NHS Digital will be used.
In order to work out the cost of this care after discharge from the neonatal unit , the OptiPREM team will need to have a link between each baby born in this gestational age group, and their HES and Mortality record, held at NHS Digital. This information will be linked using their identifiers such as NHS number.
With the NHS Digital data, the team will be looking at Hospital Episode Statistics Outpatients, Hospital Episode Statistics Critical Care, HES: Civil Registration (Deaths) bridge, Civil Registration (Deaths) - Secondary Care Cut, and Hospital Episode Statistics Admitted Patient Care. This analysis will include calculating the cost of care from daily episodes of care for each baby in each gestational age group, and then comparing the overall costs of care for those babies born in a Local Neonatal unit, and those babies born in a neonatal intensive care unit (two types of units).
Justification for the work- how NHS Digital linkage will help OptiPrem project aims:
• Linking NHS Digital data on each baby from the time of birth, through discharge from a neonatal unit (i.e. NNRD held information on babies born between 27-31 weeks gestation in England), to hospital episodes statistics and mortality up to two year of age for each baby (i.e. NHS digital records) will help to assess costs of care using population-based outcomes up to 2 year of age, in workstream 3 of the OptiPrem project.
• Linking neonatal patient records to subsequent HES patient records and civil registration mortality data up to two years of life helps the OptiPrem research team make a reasonably informed decision on what impact the place of care at birth or neonatal period has, on the subsequent mortality and hospital episodes needed for babies born between 27 and 31 weeks. This will also help the organisation examine post discharge morbidity, resource utilization, readmission rates and secondary care activity. This work will help set standards for the country on where babies should be born and cared for between 27-31 weeks gestation.
Relevant Background information:
The OptiPREM study has 5 workstreams and seeks to address best place of care for babies born between 27 -31 weeks in England by looking at mortality, morbidity, health economic cost of care up to two years of age and socio-ethnographic analysis. Workstream 3, which studies the socio economic cost of care up to two years of life, requires linkage to NHS Digital, for the reason stated above.
The details of the OptiPrem study including all workstreams can be found at https://www.royalwolverhampton.nhs.uk/research-and-development/opti-prem-improving-neonatal-service-delivery/.
The Royal Wolverhampton NHS Trust (RWT) is the sole data controller for this project working on linked HES, Mortality and OptiPREM data. RWT was awarded the grant and is the OptiPREM study sponsor and outsources the expertise from NDAU and the University of Oxford for data management and analysis respectively. The grant has been awarded to the Royal Wolverhampton NHS Trust, and the project is managed through its chief investigator, at the Royal Wolverhampton NHS Trust. All decision making around results, recommendations and outputs will be led by the Royal Wolverhampton NHS Trust.
Organisations which are analysing and preparing the data in this NHS Digital Linkage request
University of Oxford: Data processor who will be conducting the health economic analysis for this linked data between NHS digital (HES/mortality) and the NNRD OptiPrem dataset on behalf f the data controller.
The Neonatal Data Analysis Unit (NDAU): Data processor, and will be a) forming the OptiPrem dataset using the NNRD, b) will send OptiPrem dataset identifiers for the NHS digital linkage, and c) append the NHS digital HES/mortality data to the rest of the OptiPrem dataset.
LEGAL BASIS AND ETHICS:
The legal basis for processing personal data under GDPR, is to perform a task in the public interest. This is covered under Article 6(1)(e); - The Royal Wolverhampton NHS Trust (RWT) are both public bodies, and it is in the public interest that work is done into providing details on mortality rates. The personal data requested under this agreement includes information about a participant's health; these are considered as special category data, and therefore the legal basis for processing these data is processing required for scientific research purposes which is covered under Article 9(2)(j) of the GDPR.
Relevant Ethics approval for OptiPrem, NDAU and NNRD: The project is funded by the National Institute for Health Research Health Systems and Delivery Research (NIHR HS&DR) stream Project number 15/70/104) and ethical approvals are in place (IRAS Reference No 212034).
The NDAU has Research Ethics Approval (REC Reference: 16/LO/1093) and Confidential Advisory Group (CAG) approval (ECC8-05(f)/2010 for the creation of the NNRD.
The NNRD is hosted on secure Chelsea and Westminster NHS Foundation Trust servers within the Chelsea and Westminster Campus of Imperial College. The NDAU extracts the data for the OptiPrem dataset from the NNRD, using these servers. The NDAU (who prepares the OptiPrem dataset) is a section within Imperial College of Science, Technology and Medicine. The team at NDAU working on the OptiPrem dataset (and supporting the NHS digital linkage) are substantive employees of NDAU, at Imperial College.
There is no separate individual consent process as this project captures data on approximately 29000 babies. Linkage of the OptiPREM data and NHS Digital data is covered by section 251. Ethical approvals for the data linkage are covered by IRAS 212034.
Expected Benefits:
The first results for this study are expected within a year of the download of the NHS digital linked two-year data. The OptiPREM study will hopefully lead to recommendations which may have an impact on the following categories.
1. Impact on babies
If the OptiPREM study's work shows a difference in morbidity and mortality, then by defining a care pathway for babies at each week of gestation from 27 to 31 weeks, the OptiPREM team may be able to develop clear guidelines to streamline delivery of care for a large number of babies in England. Individual babies may therefore benefit from receiving the most appropriate care, from the most appropriately trained staff in the centre most appropriately equipped to meet their needs. Greater standardisation of care is likely to result, which is known to have positive effects on morbidity at a population level over time; this effect could be expected for important neonatal morbidities such as infection and chronic lung disease. This is likely to be generalizable to similar settings in other developed countries.
2. Impact on mothers
Although the primary aim is to determine the most appropriate place of postnatal care for preterm babies, it is anticipated a secondary impact on the care of mothers with threatened preterm labour or pregnancy complications requiring early delivery. If the most appropriate pathway of care can be defined based on best outcomes for babies, then it will be possible, when safe to do so, for a mother to be directed or transferred to the most appropriate maternity centre for delivery of her preterm baby. The effect of this may be to reduce risks and costs associated with postnatal transfer of the baby.
3. Impact on families
a) For parents, the OptiPREM study's work may provide a clearer understanding of what to expect if their baby is born early, and where their baby is likely to be cared for. This could reduce stress and anxiety associated with preterm birth per se and the added effects of anticipated transfer of the baby for care away from home.
b) It is likely that the OptiPREM study's work will lead to changes in the pattern of postnatal transfer of babies between neonatal units. For some parents, this could mean a greater likelihood of care nearer home with reduced anxiety and costs. For those where transfer is necessary, the OptiPREM team may be able to develop strategies to better support parents based on outcomes from the qualitative work.
c) Identifying the likely personal and family costs of having a preterm baby at a specific gestation may allow families to appropriately manage their finances, either through their own resources or by seeking support from other agencies.
d) Working in partnership with parents in this study to facilitate decision making will allow parents to feel included, and to perhaps understand and accept the care pathways most appropriate for their baby.
4. Impact on neonatal clinical teams
a) Evidence-based standardisation in terms of pathways of care for these babies may mean that units become more experienced and skilled in delivering appropriate care to a selected cohort of babies.
b) Reduced mortality and morbidity are useful indicators of improvements in neonatal unit performance. Targets already exist within the National Neonatal Audit Programme (NNAP), National mortality data analysis (Mothers and Babies: Reducing Risk through Audits and Confidential Enquiries across the UK (MBRRACE) and NDAU network mortality reporting. Improved performance within a neonatal unit could boost staff morale and pump prime for continued excellence in clinical care.
5. Impact on other health care providers
a) Recommendations based from the study may be able to guide professionals in obstetrics, primary care, emergency care and ambulance services on where best to direct, if safe to do so, a mother at a specific gestation in preterm labour, so that her baby is born at a hospital with the most appropriate facilities for neonatal care.
b) Redirecting a mother to the correct maternity facility may be cost effective, as opposed to transporting a preterm baby after birth to the most appropriate neonatal unit.
6. Impact on neonatal service provision
A defined care pathway for babies born at 27-31 weeks may help ease current pressures experienced by both NICUs and LNUs in providing appropriate care for these babies. A likely impact will be less ‘blocking’ of NICU cots by preterm babies who can safely and effectively be managed in a LNU, thus freeing up NICU cot space for a neonate requiring higher intensity care. Similarly, ‘blocking’ of intensive care costs in a LNU, if the sicker more immature preterm baby is transferred out in or ex utero may be avoided.
7. Impact on Commissioning: Service and economic implications for the NHS
The OptiPREM study may reveal that changes in the configuration of neonatal services are required to obtain optimum outcomes for babies, families, and the NHS. This could have implications for cot capacity, unit designation and bed utilisation in Newborn Networks (eg. more beds in NICU vs LNU or vice versa). The OptiPREM data will support working towards a situation where care for the sickest infants is consistently provided by units most able to deliver highly specialised care and care for the less ill and more mature infants is provided in the most cost effective manner by units best equipped for this.
Appropriate re-direction of care may allow Networks and Commissioning teams the opportunity to predict future cot utilization assumptions more accurately, which could in turn better inform commissioning of neonatal cots, staff, and other resources.
The benefit of having three categories of neonatal units in England (NICU, LNU and SCBU) is currently under discussion. This research will provide information on whether a LNU facility is of benefit for babies born between 27 and 31 weeks gestation. It will contribute to a body of work that could lead to simplification of, or other changes in the current categorisation of neonatal care.
Any recommendations for change resulting from the OptiPREM study's work will therefore be evidence-based and considered from both the health benefit and cost benefit viewpoints, whilst attending to the needs of families. Implementation of any changes will require close engagement at a local level with commissioners, neonatal care providers, managers, and the general public. Should reconfiguration at a national level appear to be warranted, liaison with the BAPM will facilitate discussions and negotiations at the highest level for the management of change.
8. Impact on the NHS and society
This research has the potential to significantly reduce the costs associated with preterm birth. Although the small number of babies born at 23-26 weeks are at highest risk of serious neonatal morbidity and long-term adverse outcomes, birth at 27-31 weeks of gestation nevertheless carries a substantial risk of later chronic respiratory illness, neurological and cognitive impairment, developmental delay, behavioural problems and educational difficulties.
For the NHS, these problems represent a significant healthcare burden that, because of larger numbers of births in this gestational age range and greater survival, probably outweighs that of the group born at 23-26 weeks. Effects of preterm birth are seen throughout the whole lifespan and influence social integration, education, and employment opportunities with attendant societal consequences and financial costs.
It is now known that long-term effects of preterm birth can be modified in the most immature babies by delivering care in the most appropriate environment. It is likely that this will also be true for this slightly more mature group and that improvements in the delivery of neonatal care will have long-lasting effects that will reduce the burden of health care and societal costs in a large preterm population.
Outputs:
All outputs will contain only data that is aggregated with small numbers suppressed in line with the HES Analysis Guide
A report for the National Institute for Health Research (NIHR) HS&DR stream will be produced along with a report on recommendations to British Association Perinatal Medicine (BAPM) and the Neonatal Clinical Reference Group (CRG).
There will also be multiple submissions to peer reviewed high impact factor clinical journals on cost of care in Local Neonatal Unit (LNU) vs Neonatal Intensive Care Unit (NICU), and recommendations, in addition to presentations at National Conference e.g. British Association Perinatal Medicine regional meetings and contributions at presentation/workshops at international conferences.
Data contained in the outputs this will be aggregated at the point of output. The data will be based on the cohort studied, and this will be in the region of approx 26,000 ~ 29,000 cases, pending eligible cases after matching and exclusion.
This project will include a recommendation component (workstream 5) that will tie up all the findings in the project, including that if workstream 3, which uses NHS Digital linked data.
Key stakeholders in this workstream will include BLISS (the national parent charity for sick and preterm babies) and the national advisory body for neonatal and perinatal medicine, BAPM.
Recommendations developed will be reviewed by BLISS, the neonatal Clinical Reference Group (CRG) and the advisory body British Association of Perinatal Medicine (BAPM). Outcomes from the study will be reviewed by the stakeholders and recommendations disseminated via the stakeholders through publications, discussion, workshops, webinars, regional meetings, forums.
The output from the study will be shared via social media, presentations, webinars, seminars and lectures. The results of the study are likely to shape service delivery for neonatal units around the country. Expected target date for publication output in relation to data linkage is December 2021. This will allow adequate time for analysis of the last set of data from babies completing their 2nd birthday by December 2020. Preliminary output for Workstream 3 linked data in the form of presentations, workshops and discussion forums will begin around August 2021.
To the baby: babies will benefit from receiving the most appropriate care, from the most appropriately trained staff in the centre most appropriately equipped to meet their needs. Greater standardisation of care is likely to result, which is known to have positive effects on morbidity at a population level over time; this effect would be expected for important neonatal morbidities such as infection and chronic lung disease and other hospital related morbidity up to two years of age.
To the NHS: identifying the most cost-effective place of care will help define where it will be best to have babies born and cared for in the future. This will have a positive impact on health service delivery in the long term.
To families and staff: considering families and staff perspectives in the decision-making process for transfers will positively impact on the delivery of health service with better user satisfaction, and therefore better compliance and engagement with neonatal services overall.
It is important to note that the parent advisory panel has been involved in the development of the protocol, proof reading its final version, in the interview process for selection of clinical researchers for the study, and that the chairman of the parent panel attends and contributes to all collaborator and study steering committee meetings. The parent advisory panel will assess the face validity of the outcomes of the study, and be involved in helping deliver the scientific results in a user friendly format from the project to families. In this way this will help contribute to improvements in delivery of health services for the future.
It is expected recommendations may be available after completion of data analysis including the two-year data linked to NHS digital.
It is expected recommendations may be available after completion of data analysis including the two-year data linked to NHS digital.
Output from this may be evident by late 2021 and early 2022.
Processing:
All organisations party to this agreement must 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 i.e.: employees, agents and contractors of the Data Recipient who may have access to that data)”
To facilitate data linkage, there will be a secure data submission of patient level data for babies born at 27 to 31 weeks and discharged from neonatal care between 2014 and 2018 from the Neonatal Data Analysis Unit to NHS Digital for linkage with HES and mortality data. The following identifiers will be submitted:
• Study ID,
• NHS number,
• Sex,
• Date of birth,
• Date of birth plus 2 years
• Date of Discharge (only data from date of discharge to 2nd birthdate per baby)
Linkage of the dataset to HES and mortality data shall solely be done by NHS digital.
NHS Digital will supply an extract of linked data for these babies (Study ID + HES + mortality data) back to NDAU. This will include data for babies discharged from neonatal units between 01/01/2014 and 31/12/2018 and will include data up to the second birthday for each baby included in the study. The data requested covers HES and mortality data from 2013/2014 - 2019/2020 in one dissemination and data from 2020/2021 in another dissemination. This data will sufficiently capture all post neonatal events for up to 2 years for each date of birth for every baby in OptiPREM.
At NDAU the HES + Mortality linked data will be downloaded and there after shall be appended to the rest of the OptiPrem variables via Study ID to form a linked HES + Mortality + OptiPrem dataset.
The Study ID, which was created only for the sole purpose of linkage, will be used to trace back to the first unique identifier for each baby, a pseudonymised NHS number. Once this trace is complete, the Study ID will be dropped, this linked pseudonymised HES + Mortality + OptiPrem datatset will then be sent to the OptiPrem health economic team at the University of Oxford for data analysis.
There will be no un-encrypting or decrypting to reidentify babies, the team at NDAU will only use the Study ID to trace back to original unique identifier, the pseudo anonymised NHS number for each baby. This will allow the team at NDAU to present NHS Digital data with pseudonymised NHS number for baby identification. As stated earlier, this is what is well understood as a baby identifier with the OptiPREM study team.
Neonatal Data Analysis Unit transfers identifying data in an encrypted file sent over a file exchange system, with the password sent separately. After linkage, NHS Digital sends linked data to NDAU over secure electronic file transfer. All identifying data is removed by NHS Digital. This linked data is then downloaded vis secure electronic file transfer and loaded on a secure Chelsea and Westminster Hospital NHS Trust server.
The data request is limited and restricted to a cohort containing babies born in England at 27 to 31 weeks of gestation and discharged out of neonatal care between 2014 and 2018. The records requested are limited to only be from date of discharge from neonatal care up to 2 years from the date of birth for the selected cohort. Only HES admitted, critical care, out-patient and mortality data products are requested, as these will contain the paediatric records for the selected cohort. Only annual refreshes from 2013/2014 to 2020/2021 are requested, as these will contain the relevant records of up to the second birthdate of the last discharged OptiPrem baby on 31st December 2018.
HES/Mortality Data submitted by NHS digital will then be appended to OptiPrem dataset to link it and thereafter sent as an encrypted file over the file exchange system to the OptiPrem health economic team at the University of Oxford, with password sent separately.
DATA MINIMISATION
The cohort is all babies born with a gestational age between 27+0 weeks and 31+6 weeks at birth,and discharged between the time periods 01 January 2014 to 31 December 2018 in England. Data is limited to 2 years from the date of birth for individuals in the cohort.
Dataset:
The OptiPREM study team request to only obtain data from have limited to only get data from Hospital Episode Statistics (HES) Outpatients, Hospital Episode Statistics Critical Care, HES: Civil Registration (Deaths) bridge, Civil Registration (Deaths) - Secondary Care Cut, and Hospital Episode Statistics Admitted Patient Care. The OptiPREM study team believes will capture data for the paediatrics, when compared to the rest of the datasets like HES Accident and Emergency.
Years:
In this request, the OptiPREM study team has limited the number of years to 2013/2014, 2014/2015, 2015/2016, 2016/2017, 2017/2018, 2018/2019 and 2019/2021, as these sufficiently capture episodes happening between 2014 and 2020, which are the years that amount to 2 years of age of each discharged out of neonatal care between 2014 and 2018.
Filtering:
The request focuses on records for those babies that were born and admitted in England and at 27 to 31 weeks of gestation.
Episodes:
All episodes falling between 2014 and 2020 are essential to measuring clinical outcomes and cost of care each discharged out of neonatal care between 2014 and 2018.
Fields:
Not all fields have been chosen, as some do not apply to paediatrics, i.e. alcohol related variable. Some fields exist already in the NNRD, like those in the maternity section of HES Admitted Patient Care. Describing the geography of the hospital at Lower Super Output Area (LSOA)is sufficient, instead of using all the rest of the geography fields.
Cohorts:
The requested data will be linked data for only those supplied by the NDAU to NHS Digital. NDAU will supply identifiers for a cohort of approx ~26000 to 29000 babies.
There will be no data linkage undertaken with NHS Digital data provided under this agreement that is not already noted in the agreement.
Data will only be processed by substantive employees of processors listed in this agreement.