• Journal of Korean Critical Care Nursing
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• v.11 no.3
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• pp.45-57
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• 2018

Purpose : This study was performed to identify the influencing factors of unplanned intensive care unit (ICU) readmission. Methods : The study adopted a Rretrospective case control cohort design. Data were collected from the electronic medical records of 844 patients who had been discharged from the ICUs of a university hospital in Incheon from June 2014 to December 2014. Results : The study found the unplanned ICU readmission rate was to be 6.4%(n=54). From the univariate analysis revealed that, major symptoms at $1^{st}$ ICU admission, severity at $1^{st}$ ICU admission (CPSCS and APACHE II), duration of applying ventilator application during $1^{st}$ ICU admission, severity at $1^{st}$ discharge from ICU (CPSCS, APACHE II, and GCS), and application of $FiO_2$ with oxygen therapy, implementation of sputum expectoration methods, and length of stay of ICU at $1^{st}$ ICU discharge were appeared to be significant; further, decision tree model analysis revealed that while only 4 variables (sputum expectoration methods, length of stay of ICU, $FiO_2$ with oxygen therapy at $1^{st}$ ICU discharge, and major symptoms at $1^{st}$ ICU admission) were shown to be significant. Conclusions : Since sputum expectoration method was the most important factor to predictor of unplanned ICU readmission, a assessment tool for the patients' capability of sputum expectoration needs to should be developed and implemented, and standardized ICU discharge criteria, including the factors identified from the by empirical evidences, might should be developed to decrease the unplanned ICU readmission rate.

• Journal of Forest and Environmental Science
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• v.34 no.5
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• pp.412-417
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• 2018

Agroforestry is emerged as climate smart agriculture system and known to help in maintaining soil nutrient sustainability but its rate of expansion is still not appreciable. The present paper incorporates the different species under various agroforestry practices its density, growth and growing stock. The most dominated agroforestry practices in Bilaspur district identified as boundary tree based agri- silviculture (32%) followed with inside field tree based agri-silviculture (21%). Agri-horti-silvicultural system found merely in 5% farmer's field while silvo-pastoral practice in 8% fields. The result depicts that the most prevailing agroforestry tree species in non-forest area of Bilaspur comprises Acacia nilotica 36%, Butea monosperma 22%, Albizia spp 16%, Terminalia arjuna 7%, Azadirachta indica 3.5% and other species 15.5%. More than 90% farmer allows tree species growing naturally in their fields mainly for fuel wood, timber and as source of additional income as these species need not require special attention and care, while only 5% farmer's has adopted Tectona grandis, Dalbergia sissoo etc commercially for higher future return. The paper also discusses the constraints on agroforestry for enabling development of agroforestry in future.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.8-13
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• 2019

Despite technical advances in healthcare, the rates of hospital-acquired pressure injury (HAPI) are still high although many are potentially preventable. The purpose of this study was to determine whether tree-based prediction modeling is suitable for assessing the risk of HAPI in ICU patients. Retrospective cohort study has been carried out. A decision tree model was constructed with Age, Weight, eTube, diabetes, Braden score, Isolation, and Number of comorbid conditions as decision nodes. We used RStudio for model training and testing. Correct prediction rate of the final prediction model was 92.4 and the Area Under the ROC curve (AUC) was 0.699, which means there is about 70% chance that the model is able to distinguish between HAPI and non-HAPI. The results of this study has limited generalizability as the data were from a single academic institution. Our research finding shows that the data-driven tree-based prediction modeling may potentially support ICU sensitive risk assessment for HAPI prevention.

• Asia pacific journal of information systems
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• v.16 no.2
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• pp.69-84
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• 2006

Importance of Today's diffusion of integrated hospital information systems is that various and huge amount of data is being accumulated in their database systems. Many researchers have studied utilizing such hospital data. While most researches were conducted mainly for medical diagnosis, there have been insufficient studies to develop medical care cost prediction model, especially using machine learning techniques. In this research, therefore, we built a medical care cost prediction model for cancer patients using CBR (Case-Based Reasoning), one of the machine learning techniques. Its performance was compared with those of Neural Networks and Decision Tree models. As a result of the experiment, the CBR prediction model was shown to be the best in general with respect to error rate and linearity between real values and predicted values. It is believed that the medical care cost prediction model can be utilized for the effective management of limited resources in hospitals.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.22 no.2
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• pp.139-148
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• 2015

Purpose: This study was done to examine the effects of meatal care with essential oil on meatal E-coli and pH of inpatients in geriatric hospital. Methods: The participants were 40 patients admitted to J geriatric hospital in G city, Korea. Twenty patients were assigned to the experimental group and 20 to the control group. Participants in the experimental group received meatal care with essential oil (application of essential oil mixture consisting of lavender, tea tree, and frankincense). The control group received meatal care with saline. The meatal care was performed twice daily for one week in both groups. The scores for meatal odor, meatal pH and bacterial count for E-coli were measured before and after the treatment. Results: The score for meatal odor were significantly lower in the experimental group compared to the control group. The meatal pH and bacterial count for E-coli significantly decreased in the experimental group compared to the control group. Conclusion: Findings indicate that meatal care with essential oil is an effective nursing intervention to reduce meatal odor, meatal pH and bacterial count for E-coli for elderly women inpatients in geriatric hospitals.

• Journal of Korean Academy of Nursing
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• v.36 no.4
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• pp.662-670
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• 2006

Purpose. This study was performed to develop and test a decision-tree model of treatment-seeking behaviors about when Korean patients visit a doctor after experiencing stroke symptoms. Methods. The study used methodological triangulation. The model was developed based on qualitative data collected from in-depth interviews with 18 stroke patients. The model was tested using quantitative data collected from interviews and a structured questionnaire involving 150 stroke patients. The predictability of the decision-tree model was quantified as the proportion of participants who followed the pathway predicted by the model. Results. Decision outcomes of the model were categorized into immediate and delayed treatment-seeking behavior. The model was influenced by lowered consciousness, social-group influences, perceived seriousness of symptoms, past history of hypertension or stroke, and barriers to hospital visits. The predictability of the model was found to be 90.7%. Conclusions. The results from this study can help healthcare personnel understand the education needs of stroke patients regarding treatment-seeking behaviors, and hence aid in the development of educational strategies for stroke patients.

• Journal of Korean Academy of Nursing
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• v.40 no.4
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• pp.473-481
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• 2010

Purpose: This study was done to examine the effects of oral care with essential oil in improving the oral health status of hospice patients with terminal cancer. Methods: The participants were 43 patients with terminal cancer admitted to K hospital in G city, Korea. Twenty-two patients were assigned to the experimental group and 21 to the control group. Participants in the experimental group received special mouth care with essential oil (application of essential oil mixture consisting of geranium, lavender, tea tree, and peppermint). The control group received special mouth care with 0.9% saline. The special mouth care was performed twice daily for one week in both groups. The scores for subjective oral comfortness, objective oral state, and numbers of colonizing Candida albicans were measured before and after the treatment. Results: The score for subjective oral comfortness and objective oral state were significantly higher in the experimental group compared to the control group. The numbers of colonizing Candida albicans significantly decreased in the experimental group compared to the control group. Conclusion: Oral care with essential oil could be an effective oral health nursing intervention for hospice patients with terminal cancer.

• Korean Journal of Childcare and Education
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• v.18 no.5
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• pp.79-99
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• 2022

Objective: This study was conducted to examine the significant factors affecting media device addiction using the data mining technique for large-scale data from the Panel Study on Korean Children Survey (PSKC). The PSKC data of this study were gathered from the elementary school students in their 10th survey (1,286 3rd grade students). Methods: The SPSS 21.0 program was used for data mining decision tree analysis, and the results are as follows. Results: First, the most important predictor of media device addiction was planning-organization which was among the sub-factors of executive function. Second, as a result of the decision tree analysis, the children with the highest probability of addiction to media devices were ones that had difficulties in planning and organizing, had mothers with a permissive parenting attitude felt difficulties in controlling behavior, and were alone at home for more than two hours a day without any adult supervision. Conclusion/Implications: The results of this study can help guide the direction of future research related to children's addiction to media devices by exploring and analyzing factors that significantly affect children's addiction to media devices.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.539-550
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• 2018

Purpose: The purpose of this study was to find meaningful patient groups of disease using foreign patients data and analyze implemented test of the patient groups. Methods: The data was collected by foreign patients' EMR data of K university hospital. The author proposed tree-form patients' characteristic diagram through statistical methods that association rule, proportion test, clustering using prescription information and questionnaire information. Results: This study's analysis process was applied high blood data and diabetes data. Analysis showed other characteristic of meaningful patient groups in high blood and diabetes. In high blood, test implementation rate of patient group showed the differences. And in diabetes, test implementation rate of patient group and implemented test list showed differences. Conclusion: The result of this study can play a role as basic data that can be clinical testing standard in preventive aspect. Eventually, 5 dimensions of SERVQUAL will be improved by this study's process.

• Journal of Korean Academy of Nursing Administration
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• v.14 no.3
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• pp.229-240
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• 2008

Purpose: To develop the patient classification system based on the resource utilization for reimbursement of long-term care hospitals in Korea. Method: Health Insurance Review & Assessment Service (HIRA) conducted a survey in July 2006 that included 2,899 patients from 35 long-term care hospitals. To calculate resource utilization, we measured care time of direct care staff (physicians, nursing personnel, physical and occupational therapists, social workers). The survey of patient characteristics included ADL, cognitive and behavioral status, diseases and treatments. Major category criteria was developed by modified delphi method from 9 experts. Each category was divided into 2-3 groups by ADL using tree regression. Relative resource use was expressed as a case mix index (CMI) calculated as a proportion of mean resource use. Result: This patient classification system composed of 6 major categories (ultra high medical care, high medical care, medium medical care, behavioral problem, impaired cognition and reduced physical function) and 11 subgroups by ADL score. The differences of CMI between groups were statistically significant (p<.0001). Homogeneity of groups was examined by total coefficient of variation (CV) of CMI. The range of CV was 29.68-40.77%. Conclusions: This patient classification system is feasible for reimbursement of long-term care hospitals.