• Tuberculosis and Respiratory Diseases
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• v.58 no.5
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• pp.507-514
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• 2005

Background : Measurement of the $FEV_1$ and PEFR in COPD patients is a significant indicator of the disease severity, the response to treatment and the acute exacerbation. However, it is not known if PEFR can be used to determine the severity of COPD because the agreement between PEFR and $FEV_1$ in COPD patients is not well known. Methods : From September, 2003 to August, 2004, 125 out patients with COPD who were treated at the pulmonary clinic in KonKuk University Hospital were enrolled in this study. The $FEV_1$ and PEFR of each patient were measured and all the data was analyzed using SPSS. Results : The average predicted $FEV_1$ % and PEFR % was $56.98{\pm}18.21%$ and $70{\pm}27.60%$, respectively. There was linear correlation between the predicted $FEV_1$ % and predicted PEFR %. There was no correlation between age of the COPD patients and the predicted PEFR %. There was correlation between dyspnea, which is a subjective symptom of the patients, and the predicted PEFR %. Conclusion : In COPD patients, the classification of the severity by PEFR tends to underestimate the state of the disease compared with the classification of the severity by the $FEV_1$. Therefore, the classification of the severity by PEFR should be interpreted carefully in patients with severe symptoms. Once the classification of the severity has made, the follow-up examination may use the PEFR instead of the $FEV_1$.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.287-298
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• 2013

To develop a technique classifying patients based on computerized clinical data followed by validity verification by comparing with nurse's examination. Class scores were determined by nurses for a day on 348 resident patients in 7 wards of a general hospital according to KPCS-1. The class scores were simultaneously evaluated by reviewing the computerized clinical data acquired from the hospital management information system. These two class scores were both significantly different among different departments as well as disease patterns. Intraclass correlation analysis resulted a very high correlation coefficient of 0.96(p<0.01) between the two scoring methods, but the clinical data scores were somewhat higher. An automated patient classification system seemed possible to be developed in future with further enhancement of the present results based on computerized clinical data without manual scoring, which can be applied for performance evaluation as well as workforce planning.

• Journal of the Society of Disaster Information
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• v.14 no.1
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• pp.28-35
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• 2018

The following research has focused and implemented on designing a system that classifies the severity of mass casualty situations across both normal and disaster levels. The system's algorithm has implemented requirements such as accuracy as well as user convenience. The developed e-Triage System has applied various severity classification algorithms implemented from IoT concepts. In order to overcome flaws of currently used severity classification systems, the e-Triage System used electronic elements including the NFC module. By using the mobile application's severity classification algorithm the system demonstrated quick and accurate assessment of patient. Four different LED lamps visualized the severity classification results and RTS scores were portrayed through FND(Flexible Numeric Display) after a two wave classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2672-2679
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• 2012

The study was done to provide basic data of medical quality evaluation after developing the comorbidity disease mortality measurement modeled on the severity-adjustment method of AMI. This study analyzed 699,701 cases of Hospital Discharge Injury Data of 2005 and 2008, provided by the Korea Centers for Disease Control and Prevention. We used logistic regression to compare the risk-adjustment model of the Charlson Comorbidity Index with the predictability and compatibility of our severity score model that is newly developed for calibration. The models severity method included age, sex, hospitalization path, PCI presence, CABG, and 12 variables of the comorbidity disease. Predictability of the newly developed severity models, which has statistical C level of 0.796(95%CI=0.771-0.821) is higher than Charlson Comorbidity Index. This proves that there are differences of mortality, prevalence rate by method of mortality model calibration. In the future, this study outcome should be utilized more to achieve an improvement of medical quality evaluation, and also models will be developed that are considered for clinical significance and statistical compatibility.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.345-355
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• 2012

Delayed treatment of acute cardiovascular and cereb-directrovascular diseases is related to poor prognosis and sequelae. For rapid and adequate treatment, role of prehospital emergency dispatchers for adequate triage and selection of hospital is important. In several advanced countries, emergency dispatchers use standardized protocols for decision of rescuer resources or distribution of patients at each hospital. ut, there has not been developed standardized protocol for emergency dispatchers in Korea. We developed standardized protocol based on NHS-direct and CTAS system for triage of symptoms of chest pain and Stroke. Groups with standardized protocol and without protocol was compared to triage result at emergency department which patient visited. The accuracy of triage on chest pain was 70.0% in group A, 94.0% in group B(p<0.01). The accuracy of triage in stroke symptoms was 64.2% in group A, 84.6% in group B(p<0.01). Conclusion: In this study, the accuracy of telephone triage with the protocol was more accurate than without the protocol. But, more studies are needed to generalize the protocol in South korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.626-634
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• 2018

This retrospective study investigates the accuracy of triage procedures for pediatric patients in emergency departments (EDs) using the Korean Triage and Acuity Scale (KTAS). The study includes 250 randomly selected initial nursing records and clinical outcomes of pediatric patients who visited one regional ED or a local ED from October 2016 to September 2017. The collected data were analyzed by a qualified expert to determine the true triage score. The accuracy of triage was defined as the agreement between the triage score of the emergency nurses (ENs) and the true triage score as determined by the expert. Based on expert comments, the cause of the triage error was analyzed and the KTAS score was compared with the discharge, length of stay (LOS), and medical cost. The results showed that the degree of agreement in the triage score between the experts and the ENs was excellent (weighted kappa=0.77). Among the causes of triage discordance, the most frequent was the incorrect application of vital signs to the KTAS algorithm criteria (n=13). Patients with high severity KTAS levels 1 and 2 were discharged less often (${\chi}=43.25$, p<0.001). There were significant differences in the length of stay (F=12.39, p<0.001) and cost (F=11.78, p<0.001) between KTAS scores when adjusting for age. The results of this study indicate that KTAS is highly accurate in EDs. Hence, the newly developed triage tool is becoming well established in Korea.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.245-257
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• 2015

This study was to develop the predictive model for severity-adjusted mortality of inpatients with multiple chronic conditions and analyse the factors on the variation of hospital standardized mortality ratio(HSMR) to propose the plan to reduce the variation. We collect the data "Korean National Hospital Discharge In-depth Injury Survey" from 2008 to 2010 and select the final 110,700 objects of study who have chronic diseases for principal diagnosis and who are over the age of 30 with more than 2 chronic diseases including principal diagnosis. We designed a severity-adjusted mortality predictive model with using data-mining methods (logistic regression analysis, decision tree and neural network method). In this study, we used the predictive model for severity-adjusted mortality ratio by the decision tree using Elixhauser comorbidity index. As the result of the hospital standardized mortality ratio(HSMR) of inpatients with multiple chronic conditions, there were statistically significant differences in HSMR by the insurance type, bed number of hospital, and the location of hospital. We should find the method based on the result of this study to manage mortality ratio of inpatients with multiple chronic conditions efficiently as the national level. So we should make an effort to increase the quality of medical treatment for inpatients with multiple chronic diseases and to reduce growing medical expenses.

• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.509-512
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• 2010

본 논문에서는 지방환자의 서울진료의 추이와 치료결과를 살펴보기 위해 2005년, 2008년의 퇴원환자 조사 자료를 재원일수를 이용하여 분석하였다. 그 결과 2005년 퇴원환자 333,280명과 2008년 퇴원환자 419,873명의 성별, 연령별, 주진단 분포는 유사한 것으로 나타났으며 치료결과 재원일수는 2005년에 30일 이상이 7.2%, 20~29일이 5.9%인데 비해 2008년은 30일이상이 6.2%, 20~29일 6.0%로 나타나 재원일수는 절감되었다. 전체퇴원환자의 재원일수에 영향을 끼치는 요인에 대해 회귀분석 결과 연도, 성, 보험유형, 의료기관유형, 입원경로, 내원 경유, 주진단, 거주지의 효과를 통제한 후 지방환자의 진료지역에 따른 재원일수를 살펴본 결과 서울이 가장 낮은 것으로 나타났다. 또한 암환자의 재원일수에 영향을 끼치는 요인에 대해서도 연도, 성, 보험유형, 의료기관유형, 입원경로, 내원 경우, 주진단, 거주지의 효과를 통제한 후 지방환자의 진료지역에 따른 재원일수를 살펴본 결과 서울이 가장 낮은 것으로 나타났다. 즉, 지방환가 거주지에서 진료를 받는 것에 비해 서울에서 진료를 받는 것이 치료결과가 짧았다. 이는 타 지역 진료의 간접의료비 영향으로 서울지역에서 조기 퇴원하여 거주지에서 진료하였거나 서울 진료자가 중증도가 낮은 환자가 많아 재원일수가 낮을 수 있다는 것도 배제 할 수 없다. 이에 대한 중증도 보정 후 서울 진료환자의 재원일수가 낮은 요인을 분석하는 추후 연구가 필요하다.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.369-375
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• 2019

Purpose: The purpose of this convergence study is to examine the factors influencing disease related knowledge in patients with congestive heart failure. Methods: A descriptive regression design was used and the participants were 100 patients with heart failure from one general hospital in 2015. Data analysis included .multiple regression. Results: The average scores were $9.59{\pm}1.77$ for disease related knowledge. The significant factors affecting disease related knowledge were severity(${\beta}=.32$, p<.001), duration of disease diagnosis(year) (${\beta}=.30$, p=.003). The regression model explained approximately 17.3 % of disease related knowledge. Conclusion: The findings recommend that nurses have to improve health related knowledge of patients with congestive heart failure by considering severity and duration of disease diagnosis.

• Journal of the Korean Society of Radiology
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• v.6 no.2
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• pp.107-114
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• 2012

The study was conducted in patients who had undergone angiography and arterial embolization after being diagnosed with arterial bleeding among those registered with severe trauma at the admission to the department of emergency due to accidents. In the study, comparison was done between the survived group and the nonsurvived group to investigate the usefulness and the optimal performance timing of angiography and embolization as the survival-affecting factors and treatment methods for patients. The study was performed as a retrospective analysis in 45 patients who had undergone angiography and arterial embolization among those categorized as severe trauma patients from the emergency department of H hospital located in Gyeonggi-do from July, 2006 until December, 2010. The Injury Severity Score (ISS), the Revised Trauma Score (RTS), the hematocrit were the main outcome measurements. Arterial embolization was technically successful in all cases, transcatheter arterial embolization of arterial bleeding is a useful procedure in lowering the mortality and complication in severe trauma patients. and RTS, ISS, Hematocrit were the predictable early mortality factors. So bad vital sign patients must be progressed rapidly.