PARADISE Study: Longer-term outcomes

The University of Oxford requires access to the NHS England data for the purpose of the following research project:

Predicting AF after Cardiac Surgery (PARADISE Study)- A Clinical Prediction Rule for Post-operative Atrial Fibrillation in Patients Undergoing Cardiac Surgery

The following is a summary of the aims of the research project provided by the study team on behalf of the University of Oxford.

The PARADISE Study is an ongoing NIHR-funded study investigating atrial fibrillation (AF) after cardiac surgery (AFACS).

AFACS is the most common complication following cardiac surgery, with an incidence between 30% and 50%. Even though AFACS can be transient and patients are often discharged from hospital in normal sinus rhythm, patients with new-onset AFACS have a 5-fold increased risk of developing long-term AF.

The aims of this study are to:

•To develop and externally validate two prognostic models to predict postoperative atrial fibrillation (AF) after cardiac surgery using data available:

•In the pre-operative assessment clinic or on admission for surgery (PARADISE-1).

•On arrival in the post-operative care unit (PARADISE-2).

• To identify existing risk factors and prediction models for AF after cardiac surgery.

• To develop two prediction models (PARADISE-1 and PARADISE-2) using data from the Partners Research Database (PRD).

• To test the reliability of the new models using data from large UK NHS heart centres, one US hospital (Brigham), and a UK clinical trial (Tight-K).

• To use the CALIBER database and machine learning methods to identify new risk factors and to consolidate known and new risk factors through a modified Delphi process.

The longer-term outcomes associated with AF after cardiac surgery (AFACS) are unclear. The requested linkage will allow a comprehensive assessment of the association between AFACS and longer-term outcomes. Importantly, it will allow assessment of whether the existing models developed during the current PARADISE Study, or new tailored models, can estimate the risk of these outcomes. This has the potential to improve and target follow-up of patients post-cardiac surgery, providing tangible patient benefit in addition to the PARADISE study in its current form.

The following NHS England Data will be accessed:

• Hospital Episode Statistics

• Admitted Patient Care

• Outpatients

• Emergency Care Data Set (ECDS)

• Civil Registration of Death

The above data requested are necessary to obtain the the required information regarding hospital admissions and the diagnostics codes to identify the AF-related complication post AFACS.

The level of the Data will be:

• Pseudonymised

The Data will be minimised as follows:

Limited to a study cohort of all undergoing cardiac surgery from 1st October 2021 to 31st July 2023 identified by the following third party organisations as follows:

• Oxford University Hospitals NHS Foundation Trust (911 patients),

• Bart's Health NHS Trust (1228 patients),

• Liverpool Heart and Chest Hospital NHS Trust (2339 patients).

The University of Oxford is the research sponsor and the 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 the National Institute of Health Research , Health Technology Assessment Programme HTA Project. The funding is specifically for the study described.

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

The PARADISE study is an international collaboration. Study team members outside the University of Oxford may suggest analytical considerations, but the purpose and means of data processing is determined by study team members within the University of Oxford.

The PARADISE study was conducted in close collaboration with experienced patient and public representatives (PPI), who were involved from the funding application stage and throughout the project. These members have worked with the Oxford research team and contributed to ethics approval, oversight, and dissemination of results.

Organisations like StopAfib.org, the Arrhythmia Alliance, and the Atrial Fibrillation Association also supported the funding application. Three PPI members serve on the PARADISE oversight steering group, participating actively in bi-annual meetings alongside independent experts. They have also attended University of Oxford Critical Care Research Group PPI events in March and September 2023, and March 2024, where the PARADISE study was presented and discussed. These events allowed for public feedback on topics such as AF risk before surgery and the use of AI in research. PPI participants emphasised the importance of clear, unbiased communication about risk, a preference for transparency, and the use of plain language to support informed decision-making by patients and caregivers.

Oxford University Hospitals NHS Foundation Trust, Bart's Health NHS Trust and Liverpool Heart and Chest Hospital NHS Trust will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, Family Name, Given Name, Postcode and a Study ID) for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the Hospital Episode Statistics Admitted Patient Care & Outpatients, Emergency Care Data Set (ECDS) and Civil Registration of Death datasets to University of Oxford.

The Data will contain no direct identifying data items but will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient.

The Data will not be transferred to any other location.

The Data will be stored on servers at the University of Oxford.

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

The University of Oxford 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).

Remote processing will be from secure locations within the UK . The data will not leave the UK at any time

Access is restricted to employees of University of Oxford 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.

The Oxford University Hospitals NHS Foundation Trust, Bart's Health NHS Trust, and Liverpool Heart and Chest Hospital NHS Trust will simultaneously disseminate pseudonymised data, using the same pseudo ID shared with NHS England, to the University of Oxford. The University of Oxford will match the data using the pseudo ID. There will be no requirement and no attempt to reidentify individuals when using the pseudonymised dataset.

Analysts/researchers from the University of Oxford will process/analyse the Data for the purposes described above.

The expected outputs of the processing will be:

• Peer-Reviewed Publications: Submission of at least one milestone papers, including:

- The association between AFACS and long-term outcomes.

- Development of novel tailored prediction models using statistical and machine learning approaches.

• Conference Presentations: Presentation of findings at key national and international conferences, including the European Society of Cardiology Congress.

• Reports and Public Outputs:

- Updates to be delivered to the patient and public through our ICU patient forum.

- Updates through our Critical Care Research Group website.

- Press releases where appropriate

• Engagement Activities:

- Workshops and webinars targeting clinicians, policymakers, and researchers.

- Direct engagement with stakeholders, including healthcare organisations and patient advocacy groups.

- Social media campaigns to disseminate key findings to broader audiences.

These outputs will serve as a foundation for future developments, including:

- Integration of the predictive models into electronic health records (EHR) for clinical decision support.

- Open-source sharing of machine learning algorithms for further validation and refinement.

- Potential commercialisation of tools and software (not data) developed for AFACS risk stratification, fostering collaboration with industry partners.

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 first set of analyses and outputs will be completed within 12 months of receiving data, with subsequent publications and dissemination activities planned at six-month intervals thereafter. Dissemination will extend beyond the project’s completion to ensure ongoing engagement and exploitation of the study’s findings.

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.

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. Clients will need to take action based on the information provided to them in order to realise the potential improvement opportunities.

This study will enhance understanding of the long-term impact of AFACS. It has the potential to influence national and international clinical guidelines, inform healthcare policies, and guide interventions to mitigate the long-term burden of AFACS.

The study will produce a comprehensive analysis of the long-term consequences of AFACS, leveraging linked datasets from three UK hospitals. Key outputs will include predictive models tailored to AFACS-related outcomes and an evaluation of machine learning techniques for improved risk stratification. This research will significantly enhance understanding of AFACS, promoting evidence-based recommendations for post-operative management in cardiac surgery patients.

Yielded Benefits is not a requirement for new applications.