The impact of the Trauma Triage App on pre-hospital trauma triage: design and protocol of the stepped-wedge, cluster-randomized TESLA trial

Rogier van der Sluijs, Audrey A A Fiddelers, Job F Waalwijk, Johannes B Reitsma, Miranda J Dirx, Dennis den Hartog, Silvia M A A Evers, J Carel Goslings, W Margreet Hoogeveen, Koen W Lansink, Luke P H Leenen, Mark van Heijl, Martijn Poeze, Rogier van der Sluijs, Audrey A A Fiddelers, Job F Waalwijk, Johannes B Reitsma, Miranda J Dirx, Dennis den Hartog, Silvia M A A Evers, J Carel Goslings, W Margreet Hoogeveen, Koen W Lansink, Luke P H Leenen, Mark van Heijl, Martijn Poeze

Abstract

Background: Field triage of trauma patients is crucial to get the right patient to the right hospital within a particular time frame. Minimization of undertriage, overtriage, and interhospital transfer rates could substantially reduce mortality rates, life-long disabilities, and costs. Identification of patients in need of specialized trauma care is predominantly based on the judgment of Emergency Medical Services professionals and a pre-hospital triage protocol. The Trauma Triage App is a smartphone application that includes a prediction model to aid Emergency Medical Services professionals in the identification of patients in need of specialized trauma care. The aim of this trial is to assess the impact of this new digital approach to field triage on the primary endpoint undertriage.

Methods: The Trauma triage using Supervised Learning Algorithms (TESLA) trial is a stepped-wedge cluster-randomized controlled trial with eight clusters defined as Emergency Medical Services regions. These clusters are an integral part of five inclusive trauma regions. Injured patients, evaluated on-scene by an Emergency Medical Services professional, suspected of moderate to severe injuries, will be assessed for eligibility. This unidirectional crossover trial will start with a baseline period in which the default pre-hospital triage protocol is used, after which all clusters gradually implement the Trauma Triage App as an add-on to the existing triage protocol. The primary endpoint is undertriage on patient and cluster level and is defined as the transportation of a severely injured patient (Injury Severity Score ≥ 16) to a lower-level trauma center. Secondary endpoints include overtriage, hospital resource use, and a cost-utility analysis.

Discussion: The TESLA trial will assess the impact of the Trauma Triage App in clinical practice. This novel approach to field triage will give new and previously undiscovered insights into several isolated components of the diagnostic strategy to get the right trauma patient to the right hospital. The stepped-wedge design allows for within and between cluster comparisons.

Trial registration: Netherlands Trial Register, NTR7243. Registered 30 May 2018, https://www.trialregister.nl/trial/7038.

Keywords: Ambulance; Cluster-randomized; Emergency Medical Services; Impact; Prediction model; Stepped-wedge; Trauma Triage App; Triage; Trial; Unidirectional crossover.

Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

© The Author(s) 2020.

Figures

Fig. 1
Fig. 1
The stepped-wedge design of the TESLA-trial. Abbreviations: EMS, Emergency Medical Service; TTApp, Trauma Triage App
Fig. 2
Fig. 2
Service regions of the participating Emergency Medical Services
Fig. 3
Fig. 3
The Trauma Triage App. A sample of screens from the Trauma Triage App. Left: the generated score indicating the probability that a patient might be severely injured based on all predictors. Middle: an input field requesting the age of the patient in years. Right: an input field requesting the mechanism of injury

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