NHS Digital Data Release Register - reformatted

Beamtree Uk Limited projects

1 data files in total were disseminated unsafely (information about files used safely is missing for TRE/"system access" projects).

Beamtree Evolve and NHS Confederation Collaborative — DARS-NIC-774448-Q4C6X

Opt outs honoured: No (Excuses: Does not include the flow of confidential data)

Legal basis: Health and Social Care Act 2012 – s261(2)(a)

Purposes: Yes (Consultancy)

Sensitive: Non-Sensitive

When:DSA runs 2025-07 – 2028-07 2025.07 — 2025.07.

Access method: Ongoing

Data-controller type: BEAMTREE UK LIMITED

Sublicensing allowed: No

AGD/predecessor discussions: AGD minutes - 15th May 2025 final.pdf, AGD minutes - 26th June 2025 final.pdf

Datasets:

  1. Emergency Care Data Set (ECDS)
  2. Hospital Episode Statistics Admitted Patient Care (HES APC)
  3. Hospital Episode Statistics Critical Care (HES Critical Care)
  4. Hospital Episode Statistics Outpatients (HES OP)
  5. Summary Hospital-level Mortality Indicator (SHMI)

Type of data: Anonymised - ICO Code Compliant

Objectives:

Beamtree UK Limited (Beamtree) requires access to NHS England data for the purpose of creating an analytics platform for NHS acute trusts. The platform will provide performance data and trend-based forecasting, with an ability to compare local performance with peers. These insights will support a collaborative programme (the 'Evolve Collaborative' between Beamtree and the NHS Confederation) aiming to improve services, practices and processes to minimise operational and clinical risks.

The impact of the collaborative will be to improve health and care, better understand health needs, and helping to plan and evaluate services.

The following NHS England Data will be accessed:
• Hospital Episode Statistics
o Admitted Patient Care – necessary because the platform will benchmark and provide predictive analytics for data relating to admitted patient care
o Accident & Emergency – necessary because the platform will benchmark and provide predictive analytics for data relating to A&E patient care
o Critical Care – necessary because the platform will benchmark and provide predictive analytics for data relating to critical care
o Outpatients – necessary because the platform will benchmark and provide predictive analytics for data relating to outpatient care
• Emergency Care Data Set (ECDS) – necessary because the platform will benchmark and provide predictive analytics for data relating to emergency care
• Summary Hospital-level Mortality Indicator (SHMI) – necessary because necessary because the platform will benchmark and provide predictive analytics for data relating to mortality reporting

The analytics tool intends to use these datasets to provide predictive analytics that support clinical and operational quality improvement in NHS hospitals in England & Wales. The data fields requested are necessary to support the design and development of predictive analytics models that may be required for clinical and operational improvements. The dataset is used solely for this purpose, with no extraneous data collected or processed beyond what is essential for the intended analytical functions.

Beamtree have a set of approximately 90 indicators that are set within a framework of five domains that align with the Quintuple Aim of the NHS Confederation Beamtree UK Limited collaboration. The following NHS England Data will be required for the following:
• Safety: critical safety and mortality measures to monitor performance and ensure safe care is delivered across all settings.
o Hospital Episode Statistics (HES)
o Emergency Care Data Set (ECDS)
o Summary Hospital Level Mortality Indicator (SHMI)
o Office of National Statistics (ONS) Mortality Data

• Timeliness & Accessibility: overview of efficiency of care, ensuring people receive timely access to care.
o Hospital Episode Statistics (HES)
o Emergency Care Data Set (ECDS)

• Financial & Operational Sustainability: overview of measures to ensure the health system is operated sustainably.
o Hospital Episode Statistics (HES)
o Emergency Care Data Set (ECDS)

• Effectiveness and Population Health: measures preventable hospitalisations, monitoring performance and equitable access to care.
o Hospital Episode Statistics (HES)

The level of the Data will be:
• Pseudonymised

The Data will be minimised as follows:
• Limited to data between April 2021 to latest available

Beamtree require monthly extracts, once the latest available data is provided of each month after this which would ingest into the cycle and the legacy months data (from prior to 4 years and 1 month) will be destroyed

Beamtree is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above. The NHS Confederation, as a partner of Beamtree, are involved in recruiting members to the overall programme and convening supporting Learning Communities (improvement groups). The NHS Confederation does not determine the purpose or means of the data processing and therefore does not act as a Controller. Equally, the NHS Confederation will not be accessing or using the data, therefore they do not act as a Processor. Edge Health, an organisation contracted directly with Beamtree are acting as a sub-processor.

The lawful basis for processing personal data under the UK GDPR is:
Article 6(1)(f) - processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party.

Beamtree has determined the processing is necessary for its legitimate interests in being able to provide tools and services that will benefit healthcare organisations as supported by the Health and Social care act 2012.

The lawful basis for processing special category data under the UK GDPR is:
Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

This processing is in the public interest because the data will enable trusts to identify opportunities for, and initiatives which support clinical and operational improvements, thereby supporting better delivery of NHS services.

Initial funding for product development is provided by Beamtree. Revenue from member trusts will support product sustainability over time. The product is designed to deliver a direct return on investment and broader benefits realisation for member trusts, for example:
• Data insights will identify patient safety issues and inform initiatives to improve quality of care, patient safety, and resulting efficiencies (e.g. reduced length of stay and readmission rates). Predictive analytics in the platform will enable trusts to measure the impacts of these changes and make more informed decisions about resource prioritisation.
• Beamtree is working with founder trusts in a co-design process to ensure that the metrics and reporting serve the needs of trusts for, e.g., safety and quality reporting, and executive and board reporting. This will both improve efficiency of reporting and will deliver direct savings to trusts due to reduce needs for additional ad hoc reports.

Revenue from member trusts will allow Beamtree to make a commercial profit. NHS Confederation will benefit financially through revenue from subscription licences shared between Beamtree and the NHS Confederation.

Beamtree and the NHS Confederation will work with member trusts to measure benefits realisation and return on investment.

Should trusts consider that they do not see value in the programme, they are free to discontinue membership.

Amazon Web Services (AWS) provides IT hosting services to Beamtree and will store the Data as contracted by Beamtree.

Edge Health provides data analysis services to Beamtree, Edge Healths services will be utilised during the development phase of the analytics platform as to provide troubleshooting support during this period.

Data will be accessed by:
• Substantive employees of Beamtree
• Contractors – directly employed by Beamtree working on the service would be onboarded as contingent workers into Beamtree and follow all standard operating procedures and policies of a substantive employee.

Beamtree, the trusts and the NHS Confederation are working together on the feasibility of the product, as part of this, Beamtree will be engaging with the trusts’ Patient and Public Involvement and Engagement groups. In addition, the NHS Confederation will be establishing a public/patients’ group for further development and to improve the purpose of the Evolve platform. The trusts have already provided endorsement to NHS England of the Evolve platform and benefits of the programme, which Beamtree have shared with NHSE.

Expected Benefits:

The services provided to clients are expected to identify improvement opportunities which the client may then exploit by making changes to systems, processes, resources or infrastructure to improve patient experience and patient care.
The use of the data could:
• help the system to better understand the health and care needs of populations.
• lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.
• advance understanding of regional and national trends in health and social care needs.
• advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions such as obesity and diabetes.
• inform planning health services and programmes, for example to improve equity of access, experience and outcomes.
• inform decisions on how to effectively allocate and evaluate funding according to health needs.
• provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.
• support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

Evolve is designed to support trusts to improve the safety, quality and efficiency of patient care, so providing patient benefits. The data platform leverages advances AI/ machine learning and risk-adjusted modelling to forecast future trends for an individual trust on key metrics including high-impact adverse events while also providing retrospective data for performance assessment. Metrics will be developed in a co-design process with member trusts to support quality surveillance, financial efficiency and health outcomes structured across five domains:
• Safety: safe care is delivered across all settings
• Timeliness and accessibility: people receive timely and equitable access to care
• Financial and operational sustainability: the health system is operated sustainably
• People and culture: addresses workforce engagement, organizational culture, and the alignment of staff with the institution’s mission and goals
• Effectiveness and population health: people receive timely and equitable access to care.

Trusts will be able to set up interchangeable peer groups to benchmark performance and gain deeper insights at various levels: trust-wide (site-to-site) comparisons; regional benchmarking; and national benchmarking (all England).

The data and insights from the platform will support direct action by trusts and encourage further improvements through Learning Communities of trusts convened by the NHS Confederation to understand the ‘why,’ share best practices, and turn insights into action. As a result, trusts will be able to enact clear, data-driven plans that continue initiatives with strong evidence of impact; refine initiatives showing moderate effectiveness; and discontinue efforts with negligible results.

The data and insights from the platform will support direct action by trusts and encourage further improvements through Learning Communities of trusts convened by the NHS Confederation to understand the ‘why,’ share best practices, and turn insights into action. As a result, trusts will be able to enact clear, data-driven plans that continue initiatives with strong evidence of impact; refine initiatives showing moderate effectiveness; and discontinue efforts with negligible results. This provides a direct public benefit through improving the quality and efficiency of NHS services.

For example, analysis of adverse events (HACs and CHADx) in the platform can drive questions about patient outcomes and opportunities for improvement, such as: ‘Are there any emerging trends and early warning signs in certain clinical areas, conditions and cohorts that we need to be addressing sooner rather than later?’, or ‘What are the low complex, high frequency adverse events that a modest change in practice might deliver a positive impact on patient care, reduction in bed days and therefore improved patient flow?’

Use of the predictive analytics in the platform will enable trusts to leverage forecasts to obtain statistical evidence that new improvement initiatives are working. For example, in Queensland, Australia - where these predictive analytics have been used in Beamtree’s equivalent Australian programme, Health Roundtable - Townsville hospital saw increasing incidence of delirium in the Health Roundtable data, impacting patient safety, quality of care, length of stay, and hospital finances. The predictive analytics metrics were able to model the impact of the improvement initiative on delirium rates, which meant the hospital was able to quantify the effectiveness of the intervention and make a more informed decision about how to prioritise resources, providing direct benefits and a return on investment to the hospital.

Beamtree will liaise with the NHS Confederation and the participating acute trusts to promote improvement or other initiatives which have been developed based on findings from the Evolve programme. Findings will only be promoted where permission is provided by trusts.

Outputs:

The expected outputs of the processing will be:
• Production of a tool which will be made available to acute trusts under licence.

The outputs will be communicated to relevant recipients through the following dissemination channels:
• Outputs can only be reviewed and filtered through the platform

The analytics platform will be tested with data by users in up to six acute NHS trusts in September-November 2025. The platform will be made available to all NHS acute trusts under licence from November 2025.

Processing:

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA).

NHS England will provide the relevant records from HES APC, HES A&E, HES CC, HES OP, ECDS and Summary Hospital-level Mortality Indicator (SHMI) datasets to Beamtree.

The Data will contain no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The Data will not be transferred to any other location.

The Data will stored on servers at Amazon Web Services (AWS).

Beamtree stores Data on the Cloud provided by Amazon Web Services (AWS).

The Data will be accessed by authorised personnel via remote access.

The Controller must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:
- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;
- Access controls granting users the minimum level of access required are in place;
- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;
- Multifactor authentication (MFA) is required for remote access;
- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;
- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

The data will not leave or be accessed beyond the permitted territory of use in this DSA which is England and Wales

NHS Confederation is not permitted to access the Data.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will not be linked with any other data.

There will be no requirement and no attempt to reidentify individuals when using the Data.

Analysts from the Beamtree UK Limited will process and analyse the Data for the purposes described above.

Artificial Intelligence (AI)-
1. AI techniques used in this project are limited to in-house supervised and unsupervised machine learning models developed by Beamtree. No third-party AI services will access or process the data.
2. Large language models are not incorporated into the Evolve product
3. Risk adjustment and forecasting will be performed using standard machine learning techniques such as random forests, gradient boosting, GLMs, and time series models. Deep learning will be limited, if used at all, and only applied within the secure UK-based environment.
4. Hospital benchmarking will incorporate unsupervised techniques (e.g. k-means clustering) to construct peer groups based on patient-level data, rather than traditional hospital-levle characteristics.
5. All modelling and AI-related processing will be conducted solely by Beamtree data scientists within a secure, geo-locked AWS UK environment. No data will leave this environment or be shared externally for AI training.
6. Final model selection will depend on the nature and structure of the data provided. No AI techniques will be deployed until data is assessed and suitability is confirmed.

Beamtree are required to ensure that and NHS Trusts who have access to the platform adhere to the following conditions which ensure the data cannot be identified as originating from the data supplied under this DSA:

i. NHS trusts are permitted to process the data for the purpose improving services, practices and processes to minimise operational and clinical risks within their tust
ii. NHS trusts is not permitted to combine the data with other datasets which could potentially increase the risk of reidentification for individuals in the dataset;
iii. NHS trusts must not attempt to re-identify individuals in the dataset;
iv. NHS trusts must not onwardly share the dataset;
v. NHS trusts must not publish the data;
vi. The data must be limited to the fields listed in the data specification which has been shared with and authorised by NHS England.