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

Abstract

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