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Abstract
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BACKGROUND: Air medical transport (AMT) improves outcomes for severely injured patients. The decision to fly patients is complex and must consider multiple factors. Our objective was to evaluate the interaction between geography, patient and environmental factors, and emergency medical services (EMS) system resources on AMT after trauma. We hypothesize significant geographic variation in AMT utilization will be associated with varying levels of patient, environmental, and EMS resources.
METHODS: Patients transported by EMS in the Pennsylvania state trauma registry 2000-2017 were included. We used our previously developed Air Medical Prehospital Triage (AMPT, ≥2 points triage to AMT) score and Geographic EMS Index (GEMSI, higher indicates more system resources) as measures for patient factors and EMS resources respectively. A mixed-effects logistic regression model determined the association of AMT utilization with patient, system, and environmental variables.
RESULTS: There were 195,354 patients included. Fifty-five percent of variation in AMT utilization was attributed to geographic differences. Triage to AMT by the AMPT score was associated with nearly twice the odds of AMT utilization [aOR: 1.894; 95%CI: 1.765-2.032; p < 0.001]. Each one-point increase in GEMSI was associated with a 6.1% reduction in odds of AMT [0.939; 0.922-0.957; p < 0.001]. Younger age, rural location, and more severe injuries were also associated with increased odds of AMT (p < 0.05). When categorized by GEMSI level, the AMPT score and patient factors were more important for predicting AMT utilization in the middle tercile (moderate EMS resources) compared to the lower (low EMS resources) and higher tercile (high EMS resources). Weather, season, time-of-day, and traffic were all associated with AMT utilization (p < 0.05).
CONCLUSIONS: Patient, system, and environmental factors are associated with AMT utilization which varies geographically and by EMS/trauma system resource availability. A more comprehensive approach to AMT triage could reduce variation and allow more tailored efforts towards optimizing resource allocation and outcomes. LEVEL OF EVIDENCE: III, epidemiological.
Language: en |