TY - JOUR
T1 - Wearable proximity sensors for monitoring a mass casualty incident exercise: feasibility study
AU - Ozella, Laura
AU - Gauvin, Laetitia
AU - Carenzo, Luca
AU - Quaggiotto, Marco
AU - Ingrassia, Pier Luigi
AU - Tizzoni, Michele
AU - Panisson, André
AU - Colombo, Davide
AU - SAPIENZA, Anna
AU - Kalimeri, Kyriaki
AU - Corte, Francesco Della
AU - Cattuto, Ciro
PY - 2019
Y1 - 2019
N2 - Over the past several decades, naturally occurring and man-made mass casualty incidents (MCIs) have increased in frequency and number worldwide. To test the impact of such events on medical resources, simulations can provide a safe, controlled setting while replicating the chaotic environment typical of an actual disaster. A standardized method to collect and analyze data from mass casualty exercises is needed to assess preparedness and performance of the health care staff involved.
AB - Over the past several decades, naturally occurring and man-made mass casualty incidents (MCIs) have increased in frequency and number worldwide. To test the impact of such events on medical resources, simulations can provide a safe, controlled setting while replicating the chaotic environment typical of an actual disaster. A standardized method to collect and analyze data from mass casualty exercises is needed to assess preparedness and performance of the health care staff involved.
KW - contact patterns
KW - contact networks
KW - wearable proximity sensors
KW - mass casualty incident
KW - simulation
KW - medical staff – patient interaction
KW - patients’ flow
KW - contact patterns
KW - contact networks
KW - wearable proximity sensors
KW - mass casualty incident
KW - simulation
KW - medical staff – patient interaction
KW - patients’ flow
UR - https://iris.uniupo.it/handle/11579/205642
U2 - 10.2196/12251
DO - 10.2196/12251
M3 - Article
SN - 1438-8871
VL - 21
JO - JMIR. JOURNAL OF MEDICAL INTERNET RESEARCH
JF - JMIR. JOURNAL OF MEDICAL INTERNET RESEARCH
IS - 4
ER -