Examining air medical transport in interfacility emergency general surgery transfers to a quaternary center.

Background: Regionalized care has increased interfacility transfers, particularly for emergency general surgery (EGS) patients requiring urgent, specialized care. Air medical transport (AMT) provides rapid transfer with critical care capabilities and is increasingly used for EGS, but its time-saving benefits remain uncertain. This study aims to identify the population of EGS patients undergoing AMT and the distance thresholds where AMT is faster than ground transport.

Methods: We conducted a retrospective cohort and analyzed EGS patients transferred to our quaternary center from January 2021 to December 2023. Geospatial analysis was used to calculate transport distances, and linear regression assessed the association between transfer time and distance, identifying the threshold where the 95% confidence interval of AMT no longer overlapped with ground transport. We stratified the analysis by weather conditions and peak traffic times.

Results: We analyzed 1,713 EGS patients, with 26.4% undergoing AMT. Air medical transport patients were older and more frail and had higher in-hospital mortality rates (27.9% vs. 7.2%) compared with ground transport patients. The most common primary diagnosis for was unspecified sepsis, but AMT patients had more necrotizing soft tissue infections and gastrointestinal bleeds. Air medical transport became faster than ground transport at a threshold of 5.7 miles, increasing to 7.2 miles during adverse weather and 9.1 miles during peak traffic. A random-forest model identified peak traffic and patient sequential organ failure assessment (SOFA) score as key factors influencing AMT use. Sensitivity analyses showed that including transport priority and year as interaction terms increased the distance thresholds to 17.4 miles and above.

Conclusion: This is the first study to examine AMT practice patterns in EGS and quantify distance thresholds for transport efficiency. Total transfer time and choice of transport mode are significantly influenced by weather conditions and peak traffic, highlighting the need data-driven triage protocols. Such protocols will improve timely decision making and optimize patient transfers.

Level of evidence: Epidemiological; Level III.