In this study, a multiple server channel model was developed for the outpatient department at the Public

Health Clinic with a focus on the patient waiting time for having a treatment. The main objective of this study is to

determine waiting time of patient$$s flow which can be used to improve the operating performance and also

improving the quality of the services provided to the patients. The first objective to this study to determine the

waiting arrival time and service time of patients at outpatient department. This results is shown at the Table $2,3$ and

$4.$ The result stated that the average waiting time of patients in queue is $54\mathrm{.}295$ minutes with the average total exit

patient is $327$ patients. Thus, the average service time is $13\mathrm{.}481$ minutes. In comparison, a study in Malaysia found

that the average service time in outpatients was $15$ minutes $($Ba et al$.,2017).$ There is no specific guideline on the

best service length but studies found that patients prefer to have more time with the doctor.

Meanwhile the second objective is proved that this study using the simulation technique for model queuing

system. Based on the results of multiple server channel patient flow simulation model developed, it is proved that

there is waiting time achieved with Ministry of Health patient charter. In this patient charter stated that patients

should achieved the target of waiting to see the doctor within or less than $60$ minutes. Simulation model result shows

that longest waiting time exist at pre$-$consultation room about $28$ minutes and the lowest utilization of server is at

registration counter about $59\%.$ Therefore, suggested improvement need to make to this stations with a view to

reduce the waiting time and increase the utilization of server. This is to ensure the high quality of services is

delivered. The outcome of this study is the better understanding of queuing theory and management service. In

addition, the health care providers can make decision that increase the satisfaction of all relevant group besides

optimizing the resources. This study further established that queuing theory and modelling is an effective tool that

can be used to make decisions on staffing needs for optimal performance with regards to queuing challenges in

clinics. This study therefore be replicated in other clinics or other countries in order to inform clinic administrators

more on the usefulness of the application of queuing theory and modelling as a tool for improved decision making.