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

Journal: Health data science
Published Date: Mar 15, 2023

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.

Authors

  • Han Wang
    Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore.
  • Qin Xiang Ng
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
  • Shalini Arulanandam
    Singapore Civil Defence Force, Singapore.
  • Colin Tan
    Singapore Civil Defence Force, Singapore.
  • Marcus E H Ong
    Health Services Research Centre, Singapore Health Services, Singapore.
  • Mengling Feng
    Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore.

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