Building a Machine Learning-based Ambulance Dispatch Triage Model for Emergency Medical Services.

ABSTRACT:

Background

In charge of dispatching the ambulances, Emergency Medical Services (EMS) call center specialists often have difficulty deciding the acuity of a case given the information they can gather within a limited time. Although there are protocols to guide their decision-making, observed performance can still lack sensitivity and specificity. Machine learning models have been known to capture complex relationships that are subtle, and well-trained data models can yield accurate predictions in a split of a second.

Methods

In this study, we proposed a proof-of-concept approach to construct a machine learning model to better predict the acuity of emergency cases. We used more than 360,000 structured emergency call center records of cases received by the national emergency ca

SUBMITTER: Wang H 

PROVIDER: S-EPMC10880163 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature