An Intelligent System for Prioritising Emergency Services Provided for People injured in Road Traffic Accidents

Mohammad Taghi Taghavifard, Sharareh Rostam Niakan Kalhori, Pegah Farazmand, Khatereh Farazmand


Excessive road traffic accidents are the cause of referrals of a large number of injured people to hospitals. However, shortage of resources does not allow caring for all of them at the same time. Therefore, injured individuals should be prioritised by a triage unit. Patients with serious life-threatening conditions should be sent as the first priority to the emergency department to receive required care. This paper aims to design a triage model for categorising injured individuals using two different methods: Neural Network (NN) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The models were built with a data set of 3015 data designed by Iranian medical experts and were based on patients` general appearance , vital signs and chief complaints. When a patient presents to the triage unit, the system analyses the data given and patient`s emergency status can be reported straightaway. This reduces the triage time and the queue of patients at the emergency department. Both models were tested by 3 groups of data with a total number of 417 data. Reliability and validity were assessed. Results showed that overall ANFIS model performed better in categorising patients.

DOI: 10.5901/mjss.2016.v7n1s1p354

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Mediterranean Journal of Social Sciences ISSN 2039-9340(Print) ISSN 2039-2117(Online)

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