Optimizing Patient Transport: Evaluating and Simplifying Decision Making in EMS

Presenter

Kyle Valade

Campus

UMass Amherst

Sponsor

Steven D. Brewer, Department of Biology, UMass Amherst

Schedule

Session 1, 10:30 AM - 11:15 AM [Schedule by Time][Poster Grid for Time/Location]

Location

Poster Board A78, Campus Center Auditorium, Row 4 (A61-A80) [Poster Location Map]

Abstract

Emergency Medical Services (EMS) often serve as the first point of contact regarding emergency healthcare. Under this system, EMS personnel are dispatched to an emergency, where they then assess, treat, and transport the patient to what is termed the “closest appropriate facility.” This is defined as the facility—typically a hospital—located nearest to the patient that is most adequately equipped to treat the patient’s condition. Generally, the three most important factors to account for when determining the destination of a patient are travel time to nearby facilities, the current volume of patients at each nearby facility, and the condition of the patient as it relates to the treatment capabilities of each facility. In some cases, all relevant information may not be available to the provider when determining where to bring the patient, leaving opportunity for error or suboptimal decision making. The aim of this project was to create a device that would gather all available and relevant information—travel time, facility volume, and patient condition—, streamlining the decision-making process and reducing the influence of human error. I constructed this device using consumer microcontrollers and single-board computers. This project highlights the importance of accounting for as much information as possible prior to making transport decisions for patients, as well as demonstrating how different situations and locations may affect the determination of the closest appropriate facility. In a broader context, this study seeks to inform better EMS decisions and potentially provide a model for a similar device that could be employed on active ambulances.

Keywords

emergency medical services, ambulance, arduino/raspberry pi

Research Area

Medical Sciences

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