Abstract
The emergency department (ED) of a hospital is an important unit that deals with time-sensitive and life-threatening medical cases. Rapid treatment and accuracy in diagnosis are considered the main characteristics of excellent operational processes in ED. However, in reality, long waiting time and uncertainty in the diagnosis has affected the quality of ED services. Nonetheless, these problems can be improved by utilising computing technologies that assist medical professionals to make fast and accurate decisions. This paper investigates the issues of under-treatment and uncertainty condition of acute asthma cases in ED. A novel approach, known as the fuzzy logic principle is employed to determine the severity of acute asthma. The fuzzy set theory, known as Fuzzy Rule-based Expert System for Asthma Severity (FRESAS) determination is embedded into the expert system (ES) to assess the severity of asthma among patients in ED. The proposed fuzzy methodology effectively manages the fuzziness of the patient’s information data, and determines the subjective judgment of medical practitioners’ level on eight criteria assessed in severity determination. Knowledge acquisition and representation, fuzzification, fuzzy inference engine, and defuzzification are the processes tested by the FRESAS development that incorporates expert advice. The system evaluation is performed by using datasets that were extracted from the ED clerking notes from one of the hospitals in Northern Peninsular Malaysia. System evaluation demonstrates that the proposed system performs efficiently in determining the severity of acute asthma. Furthermore, the proposed system offers opportunities for further research on other types of diseases in ED, and improves other hybridisation approaches.
Highlights
The emergency department (ED) is a unit in the hospital that assesses and treats unscheduled patients arriving for immediate treatment
The adult acute asthma cases were selected to be incorporated into the expert system (ES) due to its ability to fulfil the criteria needed for ES development, and the immediate need to obtain fast and accurate decisions in asthma management
This study proposed an uncertainty model framework, known as a fuzzy rule-based ES
Summary
The emergency department (ED) is a unit in the hospital that assesses and treats unscheduled patients arriving for immediate treatment. Apart from conducting emergency treatments, accurate diagnosis is a critical aspect of excellent services in the ED. With the evolution of computerised systems, the incorporation of an expert system would assist medical decision-making processes in ED. This paper focuses on the development of an expert system (ES) for asthma severity identification in the ED. The asthma cases were chosen as the medical domain to be investigated, instead of the many other cases at the ED as the boundaries of asthma studies are carefully identified. The adult acute asthma cases were selected to be incorporated into the ES due to its ability to fulfil the criteria needed for ES development, and the immediate need to obtain fast and accurate decisions in asthma management
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