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Abstract
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PURPOSE
Identification and triage of severely injured patients to trauma centers is paramount to survival. Many patients are undertriaged in rural areas and do not receive proper care. The decision-making processes involved in triage are not well understood and should be assessed to improve the triage process and outcomes.
Methods
Triage decision-making processes were explored through emergency medical services (EMS) practitioner focus groups and a discrete choice experiment (DCE). Attributes of trauma determined from focus groups and the literature included patient demography, injury mechanism, and trauma center distance. DCE data were analyzed using mixed logit models.
Results
High-risk mechanism, decreased age, multiple comorbidities, and pregnancy were found to increase the preference for triage. Greater trauma center distance was found to decrease preference for triage, but practitioners were willing to trade off up to 2 h of travel time to transport a third-trimester pregnancy and 48 min of travel time to transport a 25-y-old than they would a 50-y-old with the same comorbidities, injuries, and stability.
Conclusions
Our findings suggest that current forms of EMS protocols may not be appropriately tailored to support the mechanisms underlying practitioner decision making. Public health professionals and researchers should consider using DCEs to better understand EMS practitioner decision making and identify structures and incentives that may improve patient outcomes and optimally guide appropriate triage decisions.
Highlights
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Discrete choice experiments are an effective method to elicit prehospital practitioners' preferences around transport of the traumatized patient.
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Practitioner biases observed in EMS transport data are recovered in stated preference models incorporating individual preference heterogeneity.
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There is a discrepancy between the triage priorities recommended by protocol and those measured from prehospital practitioners' decisions--this may have implications in over- and undertriage rates and prehospital protocol design.
Language: en |