Effectiveness of Five-Level Prehospital Taiwan Triage and Acuity Scale (TTAS-PH) in Emergency Medical Services for Patient Outcome Prediction: A Retrospective Cohort Study.

Authors

Jui-Fan Kao, Yung-Hsiang Chang, Cheng-Yu Chien, Chip-Jin Ng, Chien-Hsiung Huang

Published in

International journal of general medicine. Volume 19. Pages 619445. Epub Jul 28, 2026.

Abstract

Triage is a cornerstone of modern emergency medicine. This study aimed to evaluate the predictive validity of the five-level Prehospital Taiwan Triage and Acuity Scale (TTAS-PH) for emergency department (ED) patient outcomes-specifically hospital admission, mortality, and ED length of stay (LOS)-compared to the former two-level system.
This retrospective cohort study included 9,698 adult patients transported by Emergency Medical Services (EMS) to a tertiary academic medical center in Taoyuan City, Taiwan, during 2023. Logistic and linear regression models were utilized to analyze the impact of variables on clinical outcomes and ED LOS. Furthermore, Receiver Operating Characteristic (ROC) curve analysis evaluated the predictive performance of the triage systems.
Male gender, older age, and higher TTAS-PH acuity levels (Levels 1 and 2) were significantly associated with worse ED outcomes and longer ED LOS. TTAS-PH Level 1 patients faced drastically elevated risks of death (OR=83.9); while they represented only 10.72% of the cohort, they accounted for 79.59% of all ED deaths. Notably, a discrepancy was observed in high-acuity (Levels 1-2) classification between the prehospital TTAS-PH (43%) and the in-hospital TTAS (8.7%). In predicting mortality, TTAS-PH demonstrated superior accuracy (AUROC=0.8829) compared to the traditional TPTS (AUROC=0.8296).
The TTAS-PH system offers robust prehospital risk stratification, demonstrating superior predictive performance compared to the traditional TPTS. By functioning as a critical early warning mechanism, TTAS-PH facilitates proactive resource mobilization, effectively shifting emergency care from a reactive to a preemptive model.

PMID:
42542875
Bibliographic data and abstract were imported from PubMed on 02 Aug 2026.

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