Suwimon Khansompop, MD¹, Suchada Sriyotha, BSc¹, Warada Sriphunlom, BSc¹, Paramate Kaewko, BSc¹

Background: Accurate patient triage is crucial for efficient resource management and optimal patient outcomes in emergency medical services (EMS). In Thailand, telephone triage commonly uses the Criteria-Based Dispatch (CBD) system, while emergency departments (EDs) use the Emergency Severity Index (ESI). Discrepancies between pre-hospital and in-hospital assessments can lead to over-triage, thus excessive resource use, or under-triage, thus delayed care, potentially impacting patient morbidity and mortality.

Objective: To assess the agreement between the CBD and ESI triage systems at Kalasin Hospital.

Materials and Methods: The present study was a retrospective descriptive study. Data was collected from the Emergency Medical Information System (ITEMS), dispatched records, and patient medical records of 931 patients who reported incidents via the Kalasin Provincial EMS Dispatch Center and were transported to Kalasin Hospital ED between March 1 and August 31, 2024. Data analyses included descriptive statistics, Cohen’s κ statistics to measure agreement, and chi-square or Fisher’s exact tests to examine group differences.

Results: Most patients were male (54.67%), with an average age of 54.68 years. Overall agreement between CBD and ESI was fair (89.9%, κ=0.28, 95% CI 0.22 to 0.34, p<0.001). Red codes showed higher agreement with ESI 1 to 2 (78.12%, κ=0.37, 95% CI 0.31 to 0.43, p<0.001). However, Yellow codes with ESI 3 (56.44%, κ=0.12, 95% CI 0.07 to 0.17, p<0.001) and Green codes with ESI 4 to 5 had lower agreement at 71.95% (κ=0.08, 95% CI 0.04 to 0.14, p<0.001). The overall under-triage rate was 14.61% (highest in Red codes at 35.90%). The over-triage rate was 24.38% (highest in Green codes at 58.46%) and notable in non-specific symptom groups like headache/neck pain (41.18%) and fatigue (31.03%). There was no statistically significant difference in 24-hour mortality between under-triaged and correctly triaged patients (p=0.21).

Conclusion: While the CBD system offers speed, its accuracy in triage with ESI at Kalasin Hospital was low to moderate, especially for non-specific symptoms or critical conditions that might be under-evaluated. Improving existing assessment criteria and integrating advanced technologies like artificial intelligence (e.g., machine learning, data analysis, and predictive modeling) are essential to enhance EMS efficiency and accuracy, mitigating adverse impacts on patient lives in critical situations.

Received 22 July 2025 | Revised 13 January 2026 | Accepted 20 January 2026

DOI: 10.35755/jmedassocthai.2026.4.03285