Supporting Air Versus Ground Vehicle Decisions for Interfacility Medical Transport Using Historical Data.

Patients undergoing interfacility transfers are at potentially greater risk of adverse or critical events than those in hospital, and efficient transfers play a significant role in reducing mortality and morbidity. Medical dispatchers rely on accurate estimations of transfer time in determining the most appropriate method of transportation, often either a helicopter and/or land ambulance, in situations that are characterized by high time pressure and uncertainty. In this paper, we propose the design of a datadriven decision support tool to improve dispatcher transportmode decision making. We studied the dispatch process of the air and land medical transport system in Ontario, Canada through onsite observations and developed a tool which generates transfer time estimates based on historical data. We found that dispatchers have large estimation errors, and are biased toward higher degrees of underestimation for air transfers compared with land transfers. In contrast, the proposed tool produced estimates that had significantly less error than dispatcher estimates. The estimation error for the tool was on the average 21 min less: a practically significant difference in urgent patient care. Through onsite observations and the relevant literature, we also identified factors that may influence the collaboration between the dispatcher and the tool. This research is a first attempt to study how decisions are made for interfacility medical transfers and for evaluating the accuracy of human operator estimates of these transfer times. It is also the first to demonstrate a tool's utility in comparison to existing procedures for estimating transfer times.