Using electronic health records and continuous intra-cardiac electrogram monitoring to understand cardiovascular outcomes in patients with pacemakers and defibrillators (NICOR - 25 NCR 01)

University College London (UCL) requires access to NHS England data for the purpose of the following service evaluation project:

Using electronic health records and continuous cardiac device remote sensor monitoring to understand cardiovascular outcomes in patients with arrhythmia [NICOR - 25 NCR 01].

Pacemakers and implantable cardioverter defibrillators (ICDs) are amongst the most advanced medical implants, improving outcomes and quality of life. However, every patient does not follow the same life-course. In some, the underlying heart condition can worsen, causing heart pump failure or multiple uncomfortable ICD shocks, and there is high risk of other conditions, like stroke. We do not know why and when such events happen.

Modern implants continuously monitor a range of health measurements, including detailed electrical signals recorded from wires in the heart. Uniquely, implants are linked to remote monitoring so risk markers can be used to alert clinicians.

The following is a summary of the aims of the research project provided by UCL:

Primary Objectives:

• Define ICD Use and Identify low-risk patients who currently receive ICDs but never use them.

• Predict ICD Shocks and detect patients at risk of receiving ICD shocks.

• Guide Anticoagulation Decisions and dse data to support decisions that reduce stroke risk.

• Understand Heart Pump Failure and investigate causes of heart failure in certain patients.

Secondary Objectives:

• Evaluate arrhythmia vs. non-arrhythmia mortality.

• Identify long-term mortality trends.

• Stratify outcomes by underrepresented groups (e.g. women, elderly, patients on quadruple therapy).

• Assess health inequalities in access and outcomes.

• Identify risk factors for adverse outcomes post-pacemaker implantation.

Data from the national implant registry and from detailed implant monitoring will be used to identify those patients who might suffer adverse outcomes. Advanced pattern recognition techniques (‘artificial intelligence’) will be used to identify hidden patterns in the electrical activity of the heart.

Success of the study will be measured by whether it is possible to improve criteria for implant selection and, using detailed monitoring, to improve the care of patients at high risk of further heart disease.

The following NHS England Data will be accessed:

> NICOR National Audit of Cardiac Rhythm Management (NACRM).

> NICOR National Heart Failure Audit (NHFA).

> NICOR Myocardial Ischaemia National Audit Project (MINAP).

> Hospital Episode Statistics

- Admitted Patient Care

- Accident & Emergency

- Outpatients

> Emergency Care Dataset.

> Civil Registration Mortality.

Access to these datasets is necessary to: identify patients with cardiac implantable electronic devices (CIEDs) within (NACRM); the other requested datasets will allow measurement of clinical end points, including cardiovascular outcomes and co-variates; evaluate competing arrhythmia and non-arrhythmia to inform better ICD implant selection; identify long-term mortality trends; evaluate whether health inequalities in access, or variability in outcomes are occurring; and, evaluate risk factors for patients who are likely to have an adverse outcome after a pacemaker implant.

The level of the Data will be Pseudonymised.

The Data will be minimised as follows:

• Limited to a study cohort identified by NICOR of patients contained within the National Audit of Cardiac Rhythm Management Audit (NACRM) as meeting the following criteria:

- Patients receiving heart rhythm procedures

- Patients of all ages

- English patients

• Limited to data from April 2009 to latest available data in 2025/26.

UCL is the study sponsor and sole controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller.

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 it adheres to the UK Policy Framework for Health and Social Care Research, which protects and promotes the interests of patients, service users and the public, and aims to produce generalisable and publicly available information to inform future decisions over patients’ treatments or care.

The funding is provided by British Heart Foundation. The funding is specifically for the project described. Funding is in place until 30 March 2030 with option to extend 30 March 2032 upon application.

The funder will have no ability to suppress or otherwise limit the publication of findings.

Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure back-up of data stored in UCL’s Data Safe Haven.

The project proposal was reviewed by one patient expert representative at Barts Heart Centre who will form part of a regular steering group. Patient representatives are a highly valued and long-standing members of the Domain Expert Group. This group provides regular advice to the National for Audit for Cardiac Rhythm Management which will be used for this study (the Principal Investigator, is the national audit lead). Results will be presented at the group meetings for feedback, and on publication, findings will be disseminated as part of the research outputs of the registry.

This project has been supported after peer-review by the British Heart Foundation and Medical Research Council. The study is also supported by representatives from Cardiomyopathy UK and the Arrhythmia Alliance.

The research study was supported by the NICOR Research Access Committee (RAC) on 20/08/2025.

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

The NHS England will provide the relevant records from the Civil Registrations of Death, Hospital Episode Statistics datasets, NICOR Myocardial Ischaemia National Audit Project (MINAP), NICOR National Audit of Cardiac Rhythm Management (NACRM) and NICOR National Heart Failure Audit (NHFA) to UCL. 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 be stored on the UCL Data Safe Haven on servers at UCL. UCL uses offsite back-up services provided by VIRTUS Data Centres. UCL stores data on the Cloud provided by Amazon Web Services as contracted by UCL.

Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure back-up of data stored in UCL’s Data Safe Haven. The Data will be accessed by authorised personnel onsite at the premises of UCL and 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 England/Wales at any time.

Access is restricted to employees of UCL who have authorisation from the Principal Investigator.

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.

Researchers from UCL will analyse the Data for the purposes described above.

The expected outputs of the processing will be:

• Submissions to peer reviewed journals. This is expected at a rate of 1 to 5 publications from the end of year 1 to study completion.

• Presentations to NICOR, UCL Research meetings.

• Presentations at national and international conferences.

• Publication of dashboards on UCL’s website.

• Production of risk assessment tools which will be made available to according to the funder (British Heart Foundation) and University College London’s policies.

• A database to be utilised as a resource for health research.

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:

• Journals.

• Posters and publications at national and international conferences.

• Press/media engagement where appropriate.

This study is supported by the British Heart Foundation. The Principal Investigator also works with Cardiomyopathy UK and the Arrhythmia Alliance. All stakeholders will be contacted to ensure maximal impact of this work.

Publications, posters or presentations based on these data are expected from late-2026 and will be ongoing until study completion.

The findings of this research study are expected to contribute to evidence-based decision-making for policy-makers, local decision-makers such as doctors, and patients to inform best practice to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

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 heart-related conditions.

• Support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

Enhanced understanding of quantification of life-years and quality of life, gained by implant, will particularly benefit patient groups less represented in trials. This can help to refine use of ICD therapy by minimising the number needed to treat. Detection of patients who are likely to have an adverse outcome after a pacemaker implant can help determine choice of pacemaker therapy as well as need for follow-up and management of relevant clinical features.

Harnessing device information at scale provides an opportunity to incorporate continuous ‘wearables’-type data into chronic disease follow-up, in a patient group at high risk of future cardiovascular disease.

It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients. If appropriate, risk-modelling tools for individual patients would help better decision making for resource-intensive treatments.

Clients will need to take action based on the information provided to them in order to realise the potential improvement opportunities. For example, identifying patients who may not benefit from a pacemaker or defibrillator would help reduce unnecessary implants. This would reduce the use of costly implants, reduce the risks to patients, and alleviate resources on the healthcare service.

Yielded Benefits is not a requirement for new applications.