Traffic Patterns and Emergency Medical Services Prenotification Transport Estimates in Trauma Activations

Area of Science:

• Emergency Medicine
• Trauma Care
• Healthcare Operations

Background:

• Accurate estimation of emergency medical services (EMS) transport intervals to the emergency department (ED) is crucial for patient care and resource management.
• Traffic patterns are a potential factor influencing the accuracy of these time predictions.

Purpose of the Study:

• To investigate whether traffic patterns affect the accuracy of EMS predictions for transport intervals to the ED.
• To analyze the relationship between peak traffic hours and the accuracy of estimated transport intervals (ETI) versus actual transit intervals (ATI).

Main Methods:

• A retrospective study analyzed trauma activations at an urban level one trauma center.
• Data included patients aged 18+ arriving by EMS, with ETI and ATI extracted from prenotification calls and hospital records.
• Transport during peak hours (06:00-10:00, 16:00-20:00, Mon-Fri) was compared to off-peak hours.

Main Results:

• EMS more frequently underestimated ETI (55%) compared to accurately predicting (32%) or overestimating (12%).
• This pattern of underestimation persisted during both peak (59%) and off-peak (54%) hours.
• No statistically significant difference was found in the proportion of under- or over-estimated times between peak and off-peak traffic hours (p=0.263).

Conclusions:

• The study found no significant impact of traffic patterns on the accuracy of EMS transport interval predictions for trauma patients.
• Further research is needed to understand the reasons behind the consistent underestimation of transport times.
• Identifying antecedents of underestimated intervals can lead to improved communication and support for EMS clinicians.