Spanish Emergency Services Trial Tests AI-Enhanced Telephone Triage for Critical Conditions — Implications for Australian Emergency Medicine
247 Health News Editorial
·19 May 2026
·3 min read
·clinical-trialsSpanish emergency services are testing AI-enhanced telephone triage for critical conditions including cardiac arrest and stroke. This 5-million-call study could revolutionise emergency dispatch accuracy globally.
Originally reported by ClinicalTrials.gov
References
- 1.Australian Institute of Health and Welfare. (2023). Emergency department care 2022-23 (AIHW-HSE-312). https://www.aihw.gov.au/reports/hospitals/emergency-department-care-2022-23
- 2.Centro de Emergencias Sanitarias 061 Andalucía. (2024). Proyecto trIAje: evaluación y optimización Del Triaje telefónico Mediante Modelos de Inteligencia Artificial. ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07247669
- 3.Clawson, J., Olola, C. H., Heward, A., Patterson, B., & Scott, G. (2008). Cardiac arrest predictability in seizure patients based on emergency medical dispatcher identification of previous seizure or epilepsy history. Resuscitation, 78(3), 298-302. https://doi.org/10.1016/j.resuscitation.2008.05.005
- 4.Dami, F., Golay, C., Pasquier, M., Fuchs, V., Carron, P. N., & Hugli, O. (2015). Prehospital triage accuracy in a criteria based dispatch centre. BMC Emergency Medicine, 15, 32. https://doi.org/10.1186/s12873-015-0058-x
- 5.Eastwood, K., Morgans, A., Smith, K., & Stoelwinder, J. (2016). A novel approach for managing the growing demand for ambulance services by low-acuity patients. Australian Health Review, 40(4), 378-384. https://doi.org/10.1071/AH15134
- 6.Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine learning in medicine. New England Journal of Medicine, 380(14), 1347-1358. https://doi.org/10.1056/NEJMra1814259
- 7.Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56. https://doi.org/10.1038/s41591-018-0300-7
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247 Health News Editorial
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