• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1111-1115
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• 2006

We present heuristic interpretations of the mean waiting time of $Geo^X/G/1$ vacation queues with set-up time. The heuristic interpretation of the mean waiting time is originally proposed for the continuous-time queues. We demonstrate that the heuristic approach is useful for the discrete-time queues as well.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1137-1140
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• 2005

We present the discrete-time version of the heuristic interpretation of the mean waiting time known well about the continuous-time version. The heuristic approach is mainly based on an arriving customer's viewpoint. We obtain the mean waiting time of $Geo^X/G/1$ queueing systems, including vacation queues.

• Journal of Korean Academy of Nursing Administration
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• v.16 no.3
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• pp.219-228
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• 2010

Purpose: The purpose of this study was to explore the degree of delay in waiting time, and the relationships of waiting time, patient satisfaction, and revisiting intention of outpatient in general hospitals. Methods: The data were collected from June 22 to July 4, 2009. A total of 536 outpatients who visited 21 clinics of a general hospital were subjected to evaluate the waiting time. The survey tools used were the Korea Health Industry Development Institutes (2008) tool for patient satisfaction and Reichheld & Sasser (1990) for revisiting intention. The data were analyzed by SAS version 9.1, descriptive statistics, t-test, ANOVA, and Pearson correlation coefficient. Results: The mean patient's waiting time was $28.3{\pm}30.7\;min$, the revealed mean score of patient's satisfaction was 2.92, and the revisiting intention showed was 4.56. The waiting time was negatively correlated with patient's satisfaction (r=-.10, p<.019). Patient's satisfaction was positively correlated with revisiting intention (r=-.51, p<.001). Conclusion: Waiting time management is an important factor of increasing patient's satisfaction and revisiting intention in general hospitals. It is mandatory that reservation management systems take into account the patient's characteristics of visiting outpatient department in order to shorten the real waiting time.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.639-647
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• 1998

We consider a multiclass production system processed by a single machine with cyclic order. Each part belongs to one of several classes and arrives at each queue in a Poisson process. The processing discipline at each queue is either exhaustive or gated. We introduce a new approach to analysis of mean waiting times for each queue. We formulate mean waiting times as cost functions on state of the system. The mean waiting times are obtained by solving a set of O($J^2$) linear equations, where J is the number of queues in the system. We also obtain the mean number of parts of each queue in the system at an arbitrary time. Based on this result, we plot the numerical values of the mean waiting times for several parameter settings.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.31-44
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• 1997

This paper presents an approximate analytical model to estimate the mean packet walting times at the stations in the IEEE 802, 6 subnetwork of a metropolitan area network. Each station is modeled as a two queue single server system, which serves data packets and requests from downstream stations according to the DQDB protocol. The model estimates the mean waiting time of the requests and in turn, using the discrete time work conservation law, estimates the mean waiting time for packets. Simulation experiments shows that the model accurately works even under very high traffic loads.

• Quality Improvement in Health Care
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• v.5 no.1
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• pp.28-40
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• 1998

Background : Many patients have been frequently complaining that they have to spend couples of hours in hospital on visiting outpatient clinic. Among several steps, two major time consuming steps were waiting to see a doctor and/or waiting at pharmacy to get medicine. Therefore not only to provide the proper guidance for medication or counseling on health affairs but also to make waiting time short is very important for the better hospital services. The aim of this study is to validate several time-saving processes to reduce waiting time at outpatient pharmacy and its efficacy. Methods : We surveyed the time interval actually taken to receive medicine after issuing prescription by doctors, and analyzed the data on the bases of relevant or possible causative factors. Then following processes were given to reduce waiting time and resurveyed and compared both data to validate efficacy of those processes : 1. No work-off on Monday and Tuesday 2. Work hour shift to start 30 minutes earlier 3. Changeable work shift between outpatient pharmacy and ward pharmacy according to work load 4. Use of pre-made medicines prescribed more frequently by certain doctors at certain time 5. Cooperation with doctors to use set prescriptions. Results : Before the process, mean waiting time at pharmacy was 29.2 minutes and most time consuming period was from noon to 1 PM, 3 to 4 PM, 1 to 2 PM in order of frequency. Only 37.7 % of patients could get the medicine within 20 minutes. Three times of surveys after process showed mean waiting time at pharmacy were 18.1 minutes, 19.0 minutes, and 17.6 minutes, respectively. And 72.7 %, 81.3%, and 82.2% of patients could get the medicine within 20 minutes. Conclusion : The mean waiting time was markedly reduced with above mentioned processes which applied intradepartmently event hough with little cooperation from other department. Consequently, the complaints of patients were decreased with increasing the satisfaction degree. In conclusion, those suggestions were recommanded to improve the degree of satisfaction of patients.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.1
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• pp.53-60
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• 2007

We consider the discrete-time $Geo^x/G/1$ queues under N-policy with multiple vacations (a single vacation) and setup time. In this queueing system, the server takes multiple vacations (a single vacation) whenever the system becomes empty, and he begins to serve the customers after setup time only if the queue length is at least a predetermined threshold value N. Using the heuristic approach, we derive the mean waiting time for both vacation models. We demonstrate that the heuristic approach is also useful for the discrete-time queues.

• Quality Improvement in Health Care
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• v.8 no.1
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• pp.56-72
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• 2001

Background : To shorten processing time for variety of medical affairs of the patient at the outpatient clinic of a big hospital is very important to qualify medical care of the patient. Therefore, patient's waiting time for medical examination is often utilized as a strong tool to evaluate patient satisfaction with a medical care provided. We performed this study to investigate factors delaying related with waiting time for medical examination. Methods : The data were collected from June 26 to July 30, 1999. A total 275 case of medical treatment and 5,634 patients who visited outpatient clinics of a tertiary hospital were subjected to evaluate the waiting time. The data were analyzed using frequency, t-test, ANOVA, $X^2$-test by SPSS Windows 7.5 program. Results : The mean patient's waiting time objectively evaluated ($30.9{\pm}33.9$ min) was longer than that subjectively by patient evaluated ($25.1{\pm}26.2$ min). Patient waiting time objectively evaluated was influenced by the starting time of medical examination, consultation hours, patients arriving time etc, as expected. The time discrepancy between two evaluations was influenced by several causative factors. Regarding the degree of patients accepted waiting time with the medical examination is 20 min. Conclusion : The results show that, besides the starting time of medical examination, consultation hours and patients arriving time, influence the patient's subjective evaluation of waiting time for medical examination and his satisfaction related with the service in the big hospital. In order to improve patient satisfaction related with waiting time for medical examination, it will be effective examination rather than to shorten the real processing time within the consultation room.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.53-63
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• 2018

In this paper, we analyze the waiting time of a queueing system with D-BMAP (discrete-time batch Markovian arrival process) and D-policy. Customer group or packets arrives at the system according to discrete-time Markovian arrival process, and an idle single server becomes busy when the total service time of waiting customer group exceeds the predetermined workload threshold D. Once the server starts busy period, the server provides service until there is no customer in the system. The steady-state waiting time distribution is derived in the form of a generating function. Mean waiting time is derived as a performance measure. Simulation is also performed for the purpose of verification and validation. Two simple numerical examples are shown.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.187-192
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• 2002

In this paper we consider an M/G/1 queueing system with vacation. The length of vacation period may be controlled by the waiting time of the first customer. The server goes on vacation as soon as the system is empty, and resumes service either when the waiting time of the leading customer reaches a predetermined value, or when the vacation period is expired, whichever comes first. We consider two types of vacation, say, multiple vacation type and N-policy type. We derive the steady-state distributions of the number of customers at arbitrary time and arbitrary customer's waiting time by means of decomposition property. Also, the mean lengths of busy period, idle period and a cycle time are given.