Modelling and Simulation of a Pre-hospital Emergency Care Network Using Timed Coloured Petri Nets

Modelling and Simulation of a Pre-hospital Emergency Care Network Using Timed Coloured Petri Nets

 

Content Structure of Modelling and Simulation of a Pre-hospital Emergency Care Network Using Timed Coloured Petri Nets

• The abstract contains the research problem, the objectives, methodology, results, and recommendations
• Chapter one of this thesis or project materials contains the background to the study, the research problem, the research questions, research objectives, research hypotheses, significance of the study, the scope of the study, organization of the study, and the operational definition of terms.
• Chapter two contains relevant literature on the issue under investigation. The chapter is divided into five parts which are the conceptual review, theoretical review, empirical review, conceptual framework, and gaps in research
• Chapter three contains the research design, study area, population, sample size and sampling technique, validity, reliability, source of data, operationalization of variables, research models, and data analysis method
• Chapter four contains the data analysis and the discussion of the findings
• Chapter five contains the summary of findings, conclusions, recommendations, contributions to knowledge, and recommendations for further studies.
• References: The references are in APA
• Questionnaire

 

Abstract of Modelling and Simulation of a Pre-hospital Emergency Care Network Using Timed Coloured Petri Nets

            Pre-hospital emergencynetwork serves as a major gateway to the Accident and Emergency (AE) department of  hospitals which is affected by overcrowding, and majority of projects studying pre-hospital emergency care networkdeal only with ambulance or firemanlocalisationas a means of addressing the problems confronting the Accident and Emergency (AE) department. However, this research work studied in detail the patient flow through the pre-hospital emergency carenetwork. Taking into account not only fireman and private ambulances localisation, but also the otherservices performed in this network such as Emergency call service the service of the Emergency response teamusing Timed Coloured Petri Nets.

            In developing a Timed Coloured Petri Nets (TCPN) model for a pre-hospital emergency care network, the emergency service of the State of Osun (O’ambulance) was used as a case study. The developed pre-hospital emergency care network (TCPN) model consists of five sub modules. Arrival sub module modelled the arrival of emergency calls with different health cases. Sort call sub module modelled the call desk and how emergency calls are received by the available call desk agent (perm). Perm Decision sub-module modelled the decision of call desk agent (perm) based on the emergency cases. Rescue team (RT) Decision sub module modelled the decision and intervention of Rescue team. While the Rescue-to-hospital sub-module modelled the transportation of victims to hospital.  The developed TCPN model was simulated using CPN tools. The validation of the developed TCPN model was explored by carrying out the statistical analysis between the simulated and the observed emergency call cases under study.

            The simulation results of the developed TCPN model revealed the number of emergency cases that require immediate and urgent response as 2, 6 and 19 while those that require no immediate response as 8, 22, 64 for the first, second and third simulations respectively. Revealing that some emergency calls require no immediate response and patients do not need to be taken to the hospital. Statistically, there were no significant difference between the simulated and the observed number of emergency cases that require immediate and urgent response.

 

Conclusively, this research work has been able to develop a TCPN model for studying a pre-hospital emergency care network. Also, the developed Timed Coloured Petri Nets model, through its simulation, could help in predicting the number of patients that do not need to be taken to the emergency department hence, reducing overcrowding in  hospitals.

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