• Title/Summary/Keyword: EMC(Emergency Medical Care)

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Evaluation of Shortening the Stay Time of Patients in an Emergency Medical Center (EMC) (응급실 환자의 응급의료센터 체류시간 단축프로그램 개발 및 효과)

  • Kim, Eun-Joo;Lim, Ji-Young
    • Journal of Home Health Care Nursing
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    • v.17 no.1
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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.

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Factors associated with unexpected revisit to an emergency medical center (예고되지 않은 응급의료센터 재방문에 영향을 미치는 요인 분석)

  • Lim, Mi-Sun;Kang, Hye-Young;Sub, Gil-Joon;Hong, Joon-Hyun
    • Korea Journal of Hospital Management
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    • v.10 no.2
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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.

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An Analysis of Primary Causes for Waiting for Inpatient Admission and Length of stay at Emergency Medical Center(EMC) (응급의료 센터의 체류 및 입원대기 시간 지연 요인 - 일개 의료기관을 중심으로 -)

  • Kil Suk-Yong;Kim Ok-Jun;Park Jin-Sun
    • 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.

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An Empirical Study on Emergency Medical Care Transportation Policy (응급의료 이송정책에 관한 실증적 연구)

    • Fire Science and Engineering
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    • v.17 no.4
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    • pp.42-56
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    • 2003
  • This research made a survey to 119 EMT laying stress on general contents connected with job in a frame of mutually organic cooperation system between the processes, composing Emergency Medical Care Transportation Policy in Korea, as a step before hospital, of happening emergency patients, 119 first-aid service of the spot, transportation of patients, construction of communication network etc.. As a result of analysis to that, it is found that there must be systematic devices which makes EMT not to be caught on medical dispute, a modernization of emergency equipments, professional first-aid agents, a proper personnel arrangement. Consequently, it suggests policy plan focusing on structural and functional aspect to improve an Emergency Medical Care Transportation system into a realistic one.

A Stay Time Optimization Model Emergency Medical Center (EMC) (응급의료센터 체류시간 최적화)

  • Kim, Eun-Joo;Lim, Ji-Young;Ryu, Jeong-Soon;Cho, Sun-Hee;Bae, Na-Ri;Kim, Sang-Suk
    • Journal of Home Health Care Nursing
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    • v.18 no.2
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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.

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