Evaluating and optimizing pre-hospital triage: Towards tailored decision-support

Abstract

Adequate pre-hospital trauma triage is crucial to enable optimal care in inclusive trauma systems. Transporting patients requiring specialized care to lower-level trauma centers (i.e., undertriage), results in preventable mortality and morbidity. Conversely, transporting mildly and moderately injured patients to higher-level trauma centers (i.e., overtriage), leads to unnecessary utilization of resources and costs. In general, reducing undertriage is prioritized over decreasing overtriage. The American College of Surgeons Committee on Trauma (ACSCOT) and the Dutch Health Care Institute recommend maximum undertriage rates of 5% and 10%, respectively. A recent systematic review revealed that no trauma system worldwide is currently capable of adhering to these guidelines while maintaining acceptable overtriage rates (i.e., maximum of 35%). To evaluate and improve pre-hospital trauma triage, within this thesis the Trauma Continuum of Care Cohort (TRACCC) was developed, in which eight Emergency Medical Services (EMS) and seven inclusive trauma regions participated. On-scene decision-making by EMS professionals was found to be influenced by several factors. A first pre-hospital triage decision is made at the dispatch center, and the initial assigned priority seems to affect a patient’s chance to be undertriaged. Similarly, the distance to the nearest higher-level trauma center seems to influence EMS professionals’ decision-making, as patients in need of specialized trauma care are less likely to be transported to such centers as the driving distance increases. Alternative causes for transport to a lower-level trauma centers were identified in severely injured patients who died within 30 days post-trauma: hemodynamic instability (13%) and patient requests not to receive specialized trauma care due to pre-injury health status (7%). Also, was found that secondary transfers to higher-level trauma centers occur in a minority of the undertriaged patients and may improve their survival rates. Apart from evaluating whether the absolute criteria for higher-level trauma care are present, EMS professionals assess which injuries might be present. Pre-hospital injury recognition is difficult, which was found to be especially the case in patients with serious abdominal and/or pelvic injury. Certain pre-hospital clinical factors, such as suspicion of alcohol intoxication, could be of influence on a patient’s chance to suffer from certain of injury and potentially influence injury recognition by the EMS professional. Various types of pre-hospital protocols (i.e., decision-support for pre-hospital triage in children, spinal immobilization, and administration of tranexamic acid) were found to be suboptimal in aiding Dutch EMS professionals. This could potentially be improved by implementing full prediction models in pre-hospital clinical practice. Within this thesis, such models were developed in simulated military trauma population, to provide a prioritized overview of wounded patients and to predict injuries. Additionally, the implementation of the trauma triage intervention was investigated, which involved introducing a pre-hospital prediction model, incorporated in mobile application, used as a decision-support tool by EMS professionals. The intervention resulted in a significant reduction of undertriage (5%), with no increase in overtriage. Utilizing such a model at the scene of injury to estimate the probability of a patient being severely injured is worldwide a novel and promising approach to optimize pre-hospital trauma triage.