Condition: Chest Pain · Stroke Acute · Respiratory Failure · Sponsor: Centro de Emergencias Sanitarias 061 Andalucía
Improving Telephone Triage in Emergency Calls with AI The Coordinating Centre for Urgencies and Emergencies in Andalusia (CCUE) handles thousands of calls every day. Each call needs to be assessed based on the information given over the phone to determine how serious the case is. The reasons for calling range from minor health issues to life-threatening emergencies like cardiac arrest (CPA). This project focuses on improving telephone triage for four key emergency situations that often indicate severe or life-threatening conditions: Unconsciousness / Cardiac arrest Difficulty breathing Chest pain (non-traumatic, possible heart-related issues) Stroke symptoms Our goal is to make telephone triage more accurate and efficient by using advanced Artificial Intelligence (AI) techniques, including Machine Learning (ML) and Natural Language Processing (NLP). These tools will help CCUE operators make better and faster decisions, ensuring that patients receive the right care as quickly as possible. How it will be done: The investigators will analyze anonymized historical call data from the emergency coordination system (CCR) and digital clinical records (HCDM). This includes: Structured data: Predefined fields, such as answers to standard triage questions. Unstructured data: Free-text notes and other information recorded during the call. A hybrid AI approach will be used, combining: Traditional AI methods (supervised learning and deep learning) to classify cases. Generative AI …
This description comes directly from the study's public registry record.
María José MJ Dr. Luque Hernández, MD PhD · 0034 617563352 · mariajose.luque.sspa@juntadeandalucia.es
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| Centro de Emergencias Sanitarias 061 | Málaga, Málaga, Spain | Recruiting |
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Source record: clinicaltrials.gov/study/NCT07247669