Related Experiment Video
Updated: Sep 17, 2025

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
Can Patients' characteristics influence triage Errors? A Quasi-Experimental study
Arian Zaboli1, Davide Battisti2, Marta Ziller3
1Innovation, Research and Teaching Service (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical Private University (PMU), Bolzano, Italy.
Background:
Triage error rates in emergency departments (ED) range from 10% to 30%. Despite numerous studies, it remains unclear whether certain patient characteristics are associated with triage errors. To evaluate whether patient characteristics are associated with triage errors, and whether daily auditing reduces their impact.
Methods:
A quasi-experimental study was conducted from June 2019 to June 2021 in an Italian ED. Patient characteristics were reconstructed and their association with triage errors was evaluated. Following an intervention period, during which serial audits were provided to triage nurses, the study analyzed whether patient-related variables remained associated with errors or if they changed.
Results:
The study enrolled 1,773 patients, with 904 in the pre-intervention period and 869 in the post-intervention period. In the pre-intervention period, multinomial logistic regression showed age and being accompanied to the ED were associated with lower odds of over-triage. Post-intervention, only being a tourist was associated with under-triage, and none of the previously significant variables remained associated.
Conclusions:
The study demonstrated that certain patient socio-demographic characteristics are associated with triage errors and highlighted the need for dedicated studies to evaluate which variables are linked to errors. Daily auditing emerges as a promising strategy to improve triage accuracy and promote equity in emergency care.
Related Concept Videos
Randomized Experiments
Simple randomization
Simple...
Regression Toward the Mean
Bias in Epidemiological Studies
Fundamental Attribution Error
Blind Procedures
Confounding in Epidemiological Studies

