Using machine learning to assess the extent of busy ambulances and its impact on ambulance response times: A retrospective observational study.

ABSTRACT:

Background

Ambulance response times are considered important. Busy ambulances are common, but little is known about their effect on response times.

Objective

To assess the extent of busy ambulances in Central Norway and their impact on ambulance response times.

Design

This was a retrospective observational study. We used machine learning on data from nearby incidents to assess the probability of up to five different ambulances being candidates to respond to a medical emergency incident. For each incident, the probability of a busy ambulance was estimated by summing the probabilities of candidate ambulances being busy at the time of the incident. The difference in response time that may be attributable to busy ambulances was estimated by comparing groups of nearby inci

SUBMITTER: Næss LE 

PROVIDER: S-EPMC10769093 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature