Abstract
BACKGROUND: Crowding in the emergency department (ED) is a well-known problem resulting in an increased risk of adverse outcomes. Effective triage might counteract this problem by identifying the sickest patients and ensuring early treatment. In the last two decades, systematic triage has become the standard in ED's worldwide. However, triage models are also time consuming, supported by limited evidence and could potentially be of more harm than benefit. The aim of this study is to develop a quicker triage model using data from a large cohort of unselected ED patients and evaluate if this new model is non-inferior to an existing triage model in a prospective randomized trial.
METHODS: The Copenhagen Triage Algorithm (CTA) study is a prospective two-center, cluster-randomized, cross-over, non-inferiority trial comparing CTA to the Danish Emergency Process Triage (DEPT). We include patients ≥16 years (n = 50.000) admitted to the ED in two large acute hospitals. Centers are randomly assigned to perform either CTA or DEPT triage first and then use the other triage model in the last time period. The CTA stratifies patients into 5 acuity levels in two steps. First, a scoring chart based on vital values is used to classify patients in an immediate category. Second, a clinical assessment by the ED nurse can alter the result suggested by the score up to two categories up or one down. The primary end-point is 30-day mortality and secondary end-points are length of stay, time to treatment, admission to intensive care unit, and readmission within 30 days.
DISCUSSION: If proven non-inferior to standard DEPT triage, CTA will be a faster and simpler triage model that is still able to detect the critically ill. Simplifying triage will lessen the burden for the ED staff and possibly allow faster treatment.
TRIAL REGISTRATION: Clinicaltrials.gov: NCT02698319 , registered 24. of February 2016, retrospectively registered.
Original language | English |
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Article number | 123 |
Journal | Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine |
Volume | 24 |
Number of pages | 6 |
ISSN | 1757-7241 |
DOIs | |
Publication status | Published - 10 Oct 2016 |
Keywords
- Algorithms
- Critical Illness
- Cross-Over Studies
- Denmark
- Female
- Hospital Mortality
- Humans
- Intensive Care Units
- Male
- Prospective Studies
- Survival Rate
- Triage
- Wounds and Injuries
- Journal Article
- Multicenter Study
- Randomized Controlled Trial