AI-derived ACS checklists for cardiology training: implementation barriers and ethical considerations using the CURACO framework
Abstract
Abstract Background/Introduction Acute coronary syndrome management requires rapid, systematic clinical decision-making, yet resident doctors often experience uncertainty in managing these time-sensitive presentations. Traditional checklist implementations focus primarily on clinical confidence without addressing patient empowerment, healthcare equity, or systematic integration of safety, understanding, research, authenticity, ethics, and technology. Current approaches lack holistic frameworks ensuring both clinical excellence and patient-centred care delivery. Purpose To conduct a pilot evaluation of whether AI-generated ACS checklists enhanced through CURACO principles (Clinical safety, Understanding, Research-informed care, Authentic patient-centred approaches, Conscientious ethics, and Optimised technology) improve resident doctors' confidence while incorporating patient empowerment and equity considerations. Methods We developed AI-generated ACS management checklists at our hospital, derived from ESC guidelines and enhanced using CURACO principles to ensure safety-first protocols, patient understanding components, research-informed guidelines, authentic care approaches, ethical considerations, and optimised technology integration. We surveyed resident doctors (n=15) rotating through cardiology between August 2024-February 2025 using 5-point Likert scales to assess confidence across ACS management domains before and after implementation. Paired t-tests analysed pre- and post-implementation confidence scores. Results All domains showed significant confidence improvements after implementation (p
Fields of Study & Subjects
Heart Failure Treatment and Management
Artificial Intelligence in Healthcare and Education
Machine Learning in Healthcare
Publication details
- Journal / source
- European Heart Journal - Digital Health
- Publisher
- Oxford University Press (OUP)
- Volume
- 7
- Issue
- Supplement_1
- Publication date
- 1 January 2026
- Language
- EN