• Quality Improvement in Health Care
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• v.7 no.2
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• pp.138-155
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• 2000

Background: Factors related to waiting and staying time for patient care in emergency care center (ECC) were examined during 1 month from Apr. 1 to Apr. 30, 1997 at an ECC of Yeungnam university hospital in Taegu metropolitan city, to obtain the baseline data on the strategy of effective management of emergency patients. Method: The study subjects consisted of the 1,742 patients who visited at ECC and the data were obtained from the medical records of ECC and direct surveys. Results: The mean interval between ECC admission time and initial care time by each ECC duty residents was 83.1 minutes for male patients and 84.9 minutes for female patients, and mean ECC staying time (time interval between admission and final disposition from ECC) was 718.0 minutes in men and 670.5 minutes in women. As the results, the mean staying time in ECC was higher in older age, and especially the both of initial care time and staying time were highest in patients of medical aid, and shortest in patients of worker's accident compensation insurance. The on admission or not, previously endotracheal-intubation state of patient. The ECC staying ti initial care time was much more delayed in patients of not having previous medical records and the ECC staying time was higher in referred patients from out-patient department, in transferred patients from the other hospitals and patients having previous records, and in patients partly used the order-communicating system. The factors associated with the initial care time were the numbers of ECC patients and the existence of any true emergent patients, being cardiopulmonary resuscitation (CPR) statusme was much more longer in patients of drug intoxication, in CPR patients, in medical department patients, in transfused patients and in patients related to 3 or more departments. And according to the numbers of duty internships, the ECC staying time for four internships was more longer than for five internships and after admission ordering was done, also-more longer in status being of no available beds. As above mentioned results, the factors for the ECC staying time were thought to be statistically significant (P<0.01) according to the patient's age and the laboratory orders and the X-ray films checked. And also the factor for the ECC staying time were thought to be statistically significant (P<0.01) according to the status being of no available beds, the laboratory orders and/or the special laboratory orders, the X-ray films checked, final disposing department, transferred to other hospital or not, home medication or not, admission or not, the grades of beds, the year grades of residents, the causes of ECC visit, the being CPR status on admission or not, the surgical operation or not, being known personells in our hospital. Conclution: Authors concluded that the relieving method of long-staying time in ECC was being establishing the legally proved apparatus which could differentiate the true emergency or non-emergency patients, and that the methods of shortening ECC staying time were doing definitely necessary laboratory orders and managing beds more flexibly to admit for ECC patients and finally this methods were thought to be a method of unloading for ECC personnels and improving the quality of care in emergency patients.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.62-67
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• 2003

This paper deals with a First-Come, First-Served queueing model to analyze the behavior of heterogeneous finite source system with a single server Each sources and the processor are assumed to operate in independently Markovian environments, respectively. Each request is characterized by its own exponentially distributed source and service time with parameter depending on the state of the corresponding environment, that is, the arrival and service rates are subject to random fluctuations. Our aim is to get the usual stationary performance measures of the system, such as, utilizations, mean number of requests staying at the server, mean queue lengths, average waiting and sojourn times. In the case of fast arrivals or fast service asymptotic methods can be applied. In the intermediate situations stochastic simulation Is used. As applications of this model some problems in the field of telecommunications are treated.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.6 no.3
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• pp.522-531
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• 1999

This research identifies the ingress to egress primary factors that causes a patient to receive delayed emergency medical care. This material was collected between February 1st to 28th, 1998. Research envolved 4,118 people who visited the college emergency medical center in Kyeongido Province, South Korea. Medical records were examined, using the retrospective method. to determine the length of stay and the main cause for waiting. Results are as follows : 1. The age group with the highest admission rate was 10 and under, approximately 1,394 (33.9%). Followed by an even distribution for ages between 11-50 at 10-15% for their respective ranges. The lowest admission rate was 50 years and above. 2. From the 4,118 records examined, 3,489 received outpatient treatment (84.7%); 601 were admitted for inpatient care (14.6%); 25 arrived dead on arrival (0.6%); and 4 people died at the hospital. 3. Between 7PM to 12AM, 42.9% were admitted to the EMC. The hours from 9PM to 11PM recorded the highest admission rate and 5AM to 8AM was the lowest From 8PM to 12AM, the most beds were occupied. 4. For most patients. the average length of stay was approximately 2.2 hours. By medical department, external medicine was the longest for 2.8 hours. Pediatrics was the shortest for 1.6 hours. The average waiting period for inpatient admission was 2.6 hours. Inpatient admission for pediatrics and external medicine was 3.4 hours and 2.2 hours respectively. 5. Theses are primary factors for delay at EMC: 1) pronged medical consultations to decide between inpatient versus outpatient treatment, and delaying to be inpatient, 2) when you call physicians they are delayed to come 3) Understaffing during peak or critical hours, 4) Excessive consulting with different medical departments, 5) some patients require longer monitoring periods, 6) medical records are delayed in transit between departments, 7) repeated laboratory tests make delay the result, 8) overcrowded emergency x-ray place causes delay taking x-ray and portable x-ray, 9) the distance between EMC and registration and cashier offices is too far. 10) hard to control patient's family members. The best way to reduce EMC waiting and staying time is by cooperation between departments, both medical and administrative. Each department must work beyond their job description or duty and help each other to provide the best medical service and satisfy the patient needs. The most important answer to shortened the EMC point from ingress to egress is to see things from a patient point of view and begin from there to find the solution.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.229-235
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• 2014

Improving the time and cost efficiency of production systems is one of the important means of building competitive advantage and staying profitable in the ever increasing competitive business environment. Among others, CONWIP (constant work-in-process) and DBR (drum-buffer-rope) methods are widely used in improving production process efficiency. In this study, we have developed simulation models for a real button factory production system. We have tried to improve the efficiency of the production process by implementing these two approaches to our model. According to our results, both CONWIP and DBR production approaches were found to have equivalently better results in reducing the waiting time of the bottleneck process. By applying either of the two production systems, efficiency of the real production process can be significantly improved as the simulated model results demonstrate.

• Journal of Korean Academy of Nursing
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• v.31 no.1
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• pp.68-80
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• 2001

The purpose of this study is to analyze ER patient's Triage and other statistical data. The subjects were 12,618 patients who visited the ER during the year 1998. The study showed the following results; 1. The male vs female ratio was 1.3 : 1.0, the male were in the majority (56.6%), and the age range of 20-29 old was the majority (15.3). The patients who visited ER at 8-10 pm were the majority (11.5%). On Sunday the number of patients who visited the ER were 2,189, and the majority were 17.4%. On Saturday the number of patients was visited the ER were 1,944 patients the second majority (15.4%). Their traffic means : the general passenger cars (75.5%), 119 or hospital ambulance (11.3%). 2.The reasons of visiting ER were : diseases (59.2%), injuries (23.7%). The disease vs injury ratio was 100 : 69. 3. Triage : urgent 40.7%, non-urgent 38.2%, acute 17.8%, and critical 3.2%. 4. The time of waiting and staying in the ER by the Triaget: the average time was 572 minutes (9.53 hrs.). The majority of critical patients (20.5%), acute patients (24.7%) and urgent patients (21.2%) stayed 12-24 hrs., but the majority of non-emergent (27.8%) stayed not longer than one hour. 5. Treatments by the Triage : the 42.9% of critical patients, and 61.3% of acute patients, 57.5% of urgent patients were admitted. But 91.8% of the non-emergents were discharged and 4.7% was admitted. Mortality of total ER visiter were 1.7%. DAA portion was 0.86%. 26.6% of the critical patients were DAA. DAA vs DOA ratio was 1.3 : 1.0. 6. Visiting time, monthly and seasonal distribution by the Triage : the majority of critical patients (12.2%), visited 10-12 am. The majority of acute (12.9%) and urgent (11.7%) visited 4-6 pm, but the majority of non-emergents (15.1%) visited during 8-10 pm. Autumn visiter were the majority (27.6%). The percentage of non-emergent visited in Spring was 41.4% and Autumn was 41.3%. The percentage of urgents who visited in the Summer was 45.3% and the Winter was 40.4%. By clinical departments: the 48.0% of critical patients was NS. The 45.5% of acute and the 33.6% of urgent patients were IM. But the majority of non-emergent patients was PS (21.2%), and the second majority of non-emergent patients was oral Surgery (12.8%).