Changing role of EMS -analyses of non-conveyed and conveyed patients in Finland
Paulin, Jani; Kurola, Jouni; Salanterä, Sanna; Moen, Hans; Guragain, Nischal; Koivisto, Mari; Käyhkö, Niina; Aaltonen, Venla; Iirola, Timo (2020)
Paulin, Jani
Kurola, Jouni
Salanterä, Sanna
Moen, Hans
Guragain, Nischal
Koivisto, Mari
Käyhkö, Niina
Aaltonen, Venla
Iirola, Timo
BioMed Central
2020
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2020061142727
https://urn.fi/URN:NBN:fi-fe2020061142727
Tiivistelmä
Background: Emergency Medical Services (EMS) and Emergency Departments (ED) have seen increasing
attendance rates in the last decades. Currently, EMS are increasingly assessing and treating patients without the
need to convey patients to health care facility. The aim of this study was to describe and compare the patient casemix between conveyed and non-conveyed patients and to analyze factors related to non-conveyance decision
making.
Methods: This was a prospective study design of EMS patients in Finland, and data was collected between 1st
June and 30th November 2018. Adjusted ICPC2-classification was used as the reason for care. NEWS2-points were
collected and analyzed both statistically and with a semi-supervised information extraction method. EMS patients’
geographic location and distance to health care facilities were analyzed by urban–rural classification.
attendance rates in the last decades. Currently, EMS are increasingly assessing and treating patients without the
need to convey patients to health care facility. The aim of this study was to describe and compare the patient casemix between conveyed and non-conveyed patients and to analyze factors related to non-conveyance decision
making.
Methods: This was a prospective study design of EMS patients in Finland, and data was collected between 1st
June and 30th November 2018. Adjusted ICPC2-classification was used as the reason for care. NEWS2-points were
collected and analyzed both statistically and with a semi-supervised information extraction method. EMS patients’
geographic location and distance to health care facilities were analyzed by urban–rural classification.