• 가정∙방문간호학회지
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• 제17권1호
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• pp.21-27
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• 2010

Purpose: The study evaluated a program to shorten EMC stay time. Methods: The subjects were EMC patients, and comprised a control group of 8,477 and an experimental group of 8,378. Data were collected from June 2006 to August 2007, and analyzed concerning stay time for doctor visit, decision making, and discharge. The data were analyzed by $X^2$-test and ANCOVA using SPSS14.0. Result: The stay time of doctor visit, decision making and discharge of the experimental group was significantly less compared to the control group. Using second and third grade triage criteria, the stay time of experimental group was statistically reduced from the control. Conclusion: The implemented shortening program was effective in reducing EMC stay time and increasing EMC effectiveness.

• 한국병원경영학회지
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• 제10권2호
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• pp.64-80
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• 2005

The objectives of this study were to identify factors associated with unexpected revisit to an emergency medical center (EMC) located in Seoul and to examine reasons for revisit. During March, June, September and December, 2002, a total of 168 patients had unexpected revisits to the EMC within 48 hours of a previous discharge. As a 1:1 matched control, we included 136 patients who: discharged from the EMC during the same time period: did not return to the EMC; had the same diagnosis and age(${\pm}5$) with the case. In this study, factors associated with unexpected revisits were defined as characteristics of a previous discharge, which were classified into three: sociodemographic, EMC visit-related, and discharge management factors. Reasons for revisit were categorized into disease, physician, patients, and system-related factors. Data were collected by medical chart review with assistance from clinicians of the EMC. Logistic regression results showed that patients who headed home after discharge without follow-up schedule had a 27.6 times higher risk of revisiting EMC than those who were hospitalized following EMC visit. Patients discharged on his own will had a 5.9 times higher risk of revisiting than those discharged following physician's advice. Patients requiring continual observation at the time of discharge were more likely to revisit by 8.7 times than those discharged with improved condition. About 69.13% of the revisits were due to disease-related factors, followed by 13.90% due to patient-related factors, 8.64% due to system-related factors, and 8.34% due to physician-related factors. It appears that the most significant factors influencing revisits are discharge management factors such as patient's condition at discharge, whether the discharge was accorded with physician's advice, and whether returning home without follow-up schedule. Therefore, appropriate discharge management is necessary to prevent EMC revisit.

• 기본간호학회지
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• 제6권3호
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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.

• 한국화재소방학회논문지
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• 제17권4호
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• pp.42-56
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• 2003

본 연구에서는 우리나라의 응급의료 이송정책을 구성하고 있는 병원 전 단계인 응급환자 발생에서 현장의 응급처치 단계, 환자의 이송단계, 통신망 구축단계 등의 상호 유기적인 협조체계의 기틀 속에서 119구급대원을 대상으로 직무와 관련된 일반적인 내용을 중심으로 설문조사를 실시하여 분석한 결과, 발생된 문제점으로는 구급대원들이 의료분쟁에 휘말리지 않도록 제도적 장치를 마련하여야하고, 그리고 응급 구호장비의 현대화, 구급전문 요원의 확보, 적절한 인력배치가 이루어져야 되는 것으로 조사되었다. 따라서 응급의료 이송체계를 현실적 환경에 적합한 모형으로 개선하기 위하여 구조와 기능적인 측면에 초점을 맞추어 그 정책 방안을 제안하고자 한다.

• 가정∙방문간호학회지
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• 제18권2호
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• pp.81-87
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• 2011

Purpose: The aim of this study was to estimate optimization model of stay time in EMC. Methods: Data were collected at an EMC in a hospital using medical records from June to August in 2007. The sample size was 8,378. The data were structured by stay time for doctor visit, decision making, and discharge from EMC. Descriptive statistics were used to find out general characteristics of patients. Average mean and quantile regression models were adopted to estimate optimized stay time in EMC. Results: The stay times in EMC were highly skewed and non-normal distributions. Therefore, average mean as an indicator of optimal stay time was not appropriate. The total stay time using conditional quantile regression model was estimated about 110 min, that was about 166 min shorter than estimated time using average mean. Conclusion: According to these results, we recommend to use a conditional quantile regression model to estimate optimal stay time in EMC. We suggest that this results will be used to develop a guideline to manage stay time more effectively in EMC.