Abstract
Introduction
Widespread use of smartphones allows automatic geolocalization (i.e., transmission
of location data) in countless apps. Until now, this technology has not been routinely
used in connection with an emergency call in which location data play a decisive role
This study evaluated a new software automatically providing emergency medical service
(EMS) dispatchers with a caller's geolocation. We hypothesized that this technology
will provide higher accuracy, faster dispatching of EMS and a faster beginning of
thoracic compressions in a cardiac arrest scenario.
Material and methods
Approval from the local Ethics Committee was obtained. 108 simulated emergency calls
reporting a patient in cardiac arrest were conducted at 54 metropolitan locations,
which were chosen according to a realistic pattern. At each location, a conventional
emergency call, with an oral description of the location, was given first; subsequently,
another call using an app with automatic geolocation was placed. Accuracy of localization,
time to location, time to EMS dispatch and time to first thoracic compression were
compared between both groups.
Results
The conventional emergency call was always successful (n = 54). Emergency call via
app worked successfully in n = 46 cases (85.2%). Automatic geolocation was provided
to EMS in all these n = 46 cases (100%). Deviation from estimated position to actual
position was 1173.5 ± 4343.1 m for conventional and 65.6 ± 320.5 m for automatic geolocalization
(p < 0.001). In addition, time to localization was significantly shorter using automatic
geolocalization (34.7 vs. 71.7 s, p < 0.001). Time to first thoracic compression was
significantly faster in the geolocalization group (83.0 vs. 122.6 s; p < 0.001).
Conclusions
This pilot study showed that automatic geolocalization leads to a significantly shorter
duration of the emergency call, significantly shorter times until the beginning of
thoracic compressions, and a higher precision in determining the location of an emergency.
Keywords
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Article info
Publication history
Published online: November 07, 2019
Accepted:
October 29,
2019
Received in revised form:
September 29,
2019
Received:
August 23,
2019
Identification
Copyright
© 2019 Elsevier B.V. All rights reserved.
