Can Prediction Models Triage Trauma Patients More Accurately Than Clinicians?

Title Can prediction models triage trauma patients more accurately than clinicians?

Background Nearly 5 million people die because of trauma each year. Hence trauma, defined as external injury combined with the body's associated response, is a major contributor to health issues globally. Trauma's time sensitive nature differentiates it from other health conditions. Therefore, prioritisation is crucial to treat the most urgent trauma cases first. This prioritisation is generally referred to as triage. Henceforth, formalized and non-formalized triage systems are distinguished between, where the former is defined as explicit triage consciously performed according to a priori determined criteria, and the latter as decisions on prioritisation by clinicians subconsciously taken in the absence of formalized triage.

There are two conceptually different methods currently used to triage trauma patients. Triage may be done by clinicians. Triage performed by clinicians may be affected by human factors such as tiredness and experience, yet may be viewed as the most morally appropriate method to triage trauma patients. Algorithms, such as statistical algorithms, may also be constructed for triage purpose. To predict the possibility of a certain outcome using statistical methods is called prediction modelling. Algorithms exclude human factors when triaging patients. However, algorithmic triaging may seem morally inappropriate due to the absence of human connection between the clinician and the patient.

Formalised triage systems are frequently used in trauma care in high income countries. Such systems are believed to have improved trauma care and hence trauma patient outcome. However, more than 90 per cent of all deaths due to trauma occur in low- and middle income countries, where formalised triage systems are uncommon to non-existing. Formalized triage systems may help strengthen trauma care in low - and middle income countries. However, research is lacking on whether algorithms or clinicians perform the most accurate in triaging patients.

Aim To compare the performance of prediction models with clinicians in trauma patient triage.