Proper Triage queuing system’s modeling and performance analysis is important components of Customers waiting time reduction and Hospital quality improvement. This paper develop A Cumulative Approach Modeling Technique and shows how to apply and model queuing system on Hospital Triage queuing network composed of one stations with two servers. Using Modeling Technique developed, this paper shows how to Model and analyze queuing systems and track the Analytical result of phenomenon of waiting in lines using representative measures of performance, such as average queue length, and average waiting time in queue. Beside other necessary data taken from hospital records, sample service time data of 300 patients selected randomly from both shifts and data on number of patients enter the system within one-hour time Interval for consecutive four weeks were collected to determine the service and arrival pattern of Hospital Triage. Using cumulative data collected up to time x, functions approximately fit arrival and service trend lines values were formulated and required queue values along a continuum within these discrete values were estimated. Furthermore, this paper shows how this model can be used to manage Waiting time and crowd in queue and integrate the movement of the Service into the actual operation of the resource performing the work. Finally, the author concludes that, the application of this model is feasible to drive equations and analyze phenomenon of waiting in lines; and also, this model offer better queuing systems analysis result which can be used to simulate a queuing system’s performance and allows the determination of patient appointments and effective arrival pattern management, and hence, hospital service quality improvement.
Proper Triage queuing system’s modeling and performance analysis is important components of Customers waiting time reduction and Hospital quality improvement. This paper develop A Cumulative Approach Modeling Technique and shows how to apply and model queuing system on Hospital Triage queuing network composed of one stations with two servers. Using Modeling Technique developed, this paper shows how to Model and analyze queuing systems and track the Analytical result of phenomenon of waiting in lines using representative measures of performance, such as average queue length, and average waiting time in queue. Beside other necessary data taken from hospital records, sample service time data of 300 patients selected randomly from both shifts and data on number of patients enter the system within one-hour time Interval for consecutive four weeks were collected to determine the service and arrival pattern of Hospital Triage. Using cumulative data collected up to time x, functions approximately fit arrival and service trend lines values were formulated and required queue values along a continuum within these discrete values were estimated. Furthermore, this paper shows how this model can be used to manage Waiting time and crowd in queue and integrate the movement of the Service into the actual operation of the resource performing the work. Finally, the author concludes that, the application of this model is feasible to drive equations and analyze phenomenon of waiting in lines; and also, this model offer better queuing systems analysis result which can be used to simulate a queuing system’s performance and allows the determination of patient appointments and effective arrival pattern management, and hence, hospital service quality improvement.