Evaluating pre-hospital triage and decision-making in patients who died within 30 days post-trauma: A multi-site, multi-center, cohort study

Prospective validation of a hospital triage predictive model to decrease undertriage: an EAST multicenter study

Background

Tiered trauma team activation (TTA) allows systems to optimally allocate resources to an injured patient. Target undertriage and overtriage rates of <5% and <35% are difficult for centers to achieve, and performance variability exists. The objective of this study was to optimize and externally validate a previously developed hospital trauma triage prediction model to predict the need for emergent intervention in 6 hours (NEI-6), an indicator of need for a full TTA.

Methods

The model was previously developed and internally validated using data from 31 US trauma centers. Data were collected prospectively at five sites using a mobile application which hosted the NEI-6 model. A weighted multiple logistic regression model was used to retrain and optimize the model using the original data set and a portion of data from one of the prospective sites. The remaining data from the five sites were designated for external validation. The area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC) were used to assess the validation cohort. Subanalyses were performed for age, race, and mechanism of injury.

Results

14 421 patients were included in the training data set and 2476 patients in the external validation data set across five sites. On validation, the model had an overall undertriage rate of 9.1% and overtriage rate of 53.7%, with an AUROC of 0.80 and an AUPRC of 0.63. Blunt injury had an undertriage rate of 8.8%, whereas penetrating injury had 31.2%. For those aged ≥65, the undertriage rate was 8.4%, and for Black or African American patients the undertriage rate was 7.7%.

Conclusion

The optimized and externally validated NEI-6 model approaches the recommended undertriage and overtriage rates while significantly reducing variability of TTA across centers for blunt trauma patients. The model performs well for populations that traditionally have high rates of undertriage.

Level of evidence

2.

Decision-making on the fly: a qualitative study of physicians in out-of-hospital emergency medical services

BACKGROUND

Out-of-hospital Emergency Medical Services (OHEMS) require fast and accurate assessment of patients and efficient clinical judgment in the face of uncertainty and ambiguity. Guidelines and protocols can support staff in these situations, but there is significant variability in their use. Therefore, the aim of this study was to increase our understanding of physician decision-making in OHEMS, in particular, to characterize the types of decisions made and to explore potential facilitating and hindering factors.

METHODS

Qualitative interview study of 21 physicians in a large, publicly-owned and operated OHEMS in Croatia. Data was subjected to an inductive content analysis.

RESULTS

Physicians (mostly young, female, and early in their career), made three decisions (transport, treat, and if yes on either, how) after an initial patient assessment. Decisions were influenced by patient needs, but to a greater extent by factors related to themselves and patients (microsystem), their organization (mesosystem), and the larger health system (macrosystem). This generated a high variability in quality and outcomes. Participants desired support through further training, improved guidelines, formalized feedback, supportive management, and health system process redesign to better coordinate and align care across organizational boundaries.

CONCLUSIONS

The three decisions were made complex by contextual factors that largely lay outside physician control at the mesosystem level. However, physicians still took personal responsibility for concerns more suitably addressed at the organizational level. This negatively impacted care quality and staff well-being. If managers instead adopt a learning orientation, the path from novice to expert physician could be more ably supported through organizational demands and practices aligned with real-world practice. Questions remain on how managers can better support the learning needed to improve quality, safety, and physicians' journey from novice to expert.