The challenge we’re solving
Cardiac surgery and interventions, while often life-saving, come with a high risk of complications after hospital discharge. Early signs of deterioration can go unnoticed, leading to avoidable readmissions and reduced quality of life.
The challenge: how to offer continuous, personalized follow-up that empowers patients, improves outcomes, and supports better decision-making in clinical care.
Our approach
This project brings together two tools to support recovery and risk management in cardiothoracic care:
- PROMBot-FA – a chatbot that collects patient-reported outcomes (PROMs) after atrial fibrillation ablation.
- Sends reminders and educational content.
- Complements in-person care with continuous digital follow-up.
- Deployed in the Cardiology Service at Hospital de Santa Marta.
- Causal AI Models – applied to heart failure and surgery risk.
- Clarifies cause-effect relationships between interventions and outcomes.
- Improves risk prediction and personalisation of care plans.
- Offers transparency and explainable AI to support clinical decisions.
Data collection chronogram for PROMBot-FA chatbot intervention and control groups. The red dot indicates the moment of ablation. M1, M2, and M3 indicate month 1, month 2, and month 3, respectively.
Project partners
Project goals
- Improve post-ablation monitoring using digital tools tailored to atrial fibrillation patients.
- Use PROMs to enable early detection of symptoms and reduce readmissions.
- Empower patients with targeted education and reminders.
- Apply Causal AI to enhance clinical risk management in heart failure.
- Generate evidence for scalable telemonitoring interventions in the National Health Service.
Our role
- Design and develop the PROMBot-FA chatbot to collect PROMs and support remote patient monitoring
- Coordinate its deployment at Hospital de Santa Marta, in partnership with the Cardiology Service.
- Develop Causal AI models to improve risk prediction and support transparent, data-driven clinical decisions.
- Align the entire project with value-based healthcare principles, ensuring that both patient outcomes and health system efficiency are measured and improved.
Lead researcher at VOH
The impact we hope to create
- A functional, patient-tested chatbot that supports high-value recovery.
- Real-world data on PROMs to inform adaptive, proactive care.
- Causal AI models that improve risk understanding and support safe, effective interventions.
- Stronger foundations for national telemonitoring strategies in cardiothoracic care.
