• Korea Journal of Hospital Management
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• v.15 no.4
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• pp.125-142
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• 2010

Objective : To determine demographic, clinical, health care utilization factors predicting unplanned readmission(within 28 days) to the hospital. Methods : A case-control study was conducted from January to December 2009. Multiple logistic regression was used to examine risk factors for readmission. 180 patients who had been readmitted within 28 days and 1,784 controls were recruited from an university hospital in Seoul. Results : Six risk factors associated with readmission risk were identified and include mail sex, medical service rather than surgical service, number of comorbid diseases, type of patient's room, lenth of stay, number of admissions in the prior 12 months. Conclusions : One of the association with readmission risk identified was the number of hospital admissions in the previous year. This factor may be the only risk factor necessary for assessing prior risk and has the additional advantage of being easily accessible from computerized medical records without requiring other medical record review. This risk factor may be useful in identifying a group at high readmission risk, which could be targeted in intervention studies. Multiple risk factors intervention approach should be considered in designing future prevention strategies.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.26-32
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• 2023

Hajj is a fundamental pillar of Islam that all Muslims must perform at least once in their lives. However, Umrah can be performed several times yearly, depending on people's abilities. Every year, Muslims from all over the world travel to Saudi Arabia to perform Hajj. Hajj and Umrah pilgrims face multiple issues due to the large volume of people at the same time and place during the event. Therefore, a system is needed to facilitate the people's smooth execution of Hajj and Umrah procedures. Multiple devices are already installed in Makkah, but it would be better to suggest the data architectures with the help of machine learning approaches. The proposed system analyzes the services provided to the pilgrims regarding gender, location, and foreign pilgrims. The proposed system addressed the research problem of analyzing the Hajj pilgrim dataset most effectively. In addition, Visualizations of the proposed method showed the system's performance using data architectures. Machine learning algorithms classify whether male pilgrims are more significant than female pilgrims. Several algorithms were proposed to classify the data, including logistic regression, Naive Bayes, K-nearest neighbors, decision trees, random forests, and XGBoost. The decision tree accuracy value was 62.83%, whereas K-nearest Neighbors had 62.86%; other classifiers have lower accuracy than these. The open-source dataset was analyzed using different data architectures to store the data, and then machine learning approaches were used to classify the dataset.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.203-215
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• 2019

This study was conducted to identify the utilization of public health centers, as well as the individual characteristics and regional characteristics that affect their utilization based on data from the 2016 Community Health Survey, National Statistical Portal, and National Institute of Environmental Research. Independent samples t-tests, variance analysis, and multiple logistic regression analysis were used for analysis. Hierarchical multiple regression was used to analyze individual and regional characteristics. The results of hierarchical multiple regressions revealed that aged regions, women, older age individuals, respondents with lower education level and income level, walking practitioners, nutrition label readers, individuals experiencing depression, those who have received health checkups, those who are not covered by essential care, those who have spouses, and basic livelihood beneficiaries have increased use of public health centers. However, the use of public health centers decreased in stressors, and regions in which the population per 1,000, number of health care workers, health and welfare budget, fiscal independence, and unemployment rate were above the national average. As above, the central government and local governments need to analyze not only individual characteristics such as health behavior and psychological factors, but also regional characteristics, when establishing local health care policy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.

• Journal of Korean Academy of Nursing Administration
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• v.20 no.2
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• pp.187-194
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• 2014

Purpose: The purpose of this study was to identify the perception of role transition from a student nurse to a registered nurse among senior year nursing students and to examine factors affecting their role transition. Methods: A descriptive survey with convenience sampling was conducted in four nursing colleges in Seoul, South Korea. Data were collected using a self-administrated questionnaire. Four instruments including role transition, self-esteem, interpersonal relationships and anxiety during clinical practicum were used and the students'demographics were also collected. A multiple logistic regression was used to identify predictors for the role transition. Results: A total of 233 nursing students were surveyed and final analysis was conducted utilizing 226 participants. Mean point of perceived role transition (5 point scale) was $3.34{\pm}0.44$. In a multiple regression model, high self-esteem, good interpersonal relationships, low anxiety during clinical practicum, and high satisfaction in college life were significant predictors of a smooth transition (Adj. $R^2$=.32, F=22.28, p<.001). Conclusion: The findings suggest that role transition from a student nurse to a registered nurse is facilitated through the establishment of programs to improve self-esteem and interpersonal relationships and to reduce anxiety during clinical practicum.

• Journal of Preventive Medicine and Public Health
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• v.32 no.3
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• pp.374-382
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• 1999

Objectives: Organizational culture has beer important in field of organizational behavior research for the past decade. Although there has been a growing interest in the organizational culture and organizational effectiveness, there is few research in health care field. This study was carried out to investigate the relationship of organizational culture and organizational effectiveness at general hospital. Methods: Data was collected by self-administrated questionares. Organizational cultures were measured by using Likert scale. A general hospital in Kyunggi-Do was selected and survey was conducted to 675 workers. Data was analyzed with computer package, PC-SPSS. Results: There were four types of organizational culture in this hospital consensual culture, developmental culture, hierarchical culture, rational culture. Many workers recognized their culture as rational culture and developmental culture. This finding showed that the hospital had both human related and task related climate. There were some differences in recognition of sub-organizational culture by occupational group, but perceived organizational culture was in accordance with sub-organizational culture in general. Multiple regression analysis and multiple logistic regression analysis were conducted to find the relationship of organizational culture and organizational effectiveness. As a result, developmental culture showed a strong relationship with organizational commitment and job-satisfaction. Conclusions: These results showed that types of organizational culture were significantly related to organizational effectiveness and understanding the existing culture is essential to develope their organizational effectiveness.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.21 no.3
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• pp.146-155
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• 2011

Objectives: This study was conducted to investigate the association between job stress and mental health among male and female workers in a large electric manufacture company. Methods: A cross-sectional study was carried out on 3,228 employees who participated in annual medical check-up working in a large electric manufacture company in Gyeonggi Province. Medical check-up and self-administrated questionnaire were performed at the same time. Korean Occupational Stress Scale Short Form (KOSS-SF) and Psychosocial Wellbeing Index Short Form (PWI-SF) were applied to assess occupational stress and mental health. Hierarchical multiple linear regression and multiple logistic regression were performed to estimate the association between job stress and mental health. Results: The proportion of high risk of mental health was 17.1% in male, and 46.9% in women. Job stress had a greater effect on mental health than other general and work characteristics. All subscales of job stress were revealed to affect mental health. Bad occupational climate and lack of reward are the strongest risk factors in mental health of male and female respectively. Conclusions: Our results suggest that job stress could affect mental health among large electronic manufacture workers.

• Journal of Environmental Health Sciences
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• v.36 no.6
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• pp.465-471
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• 2010

This study aims to investigate the relationship between air pollution exposure and the prevalence of allergic rhinitis in a young population in the Ulsan metropolitan region (UMR). Data on physician-diagnosed allergic rhinitis (past 12 months) in 1,449 infants and children aged 1-18 years who lived within 1.5 or 2 km of air quality monitoring sites were collected in a cross-sectional health interview survey conducted between January-February 2006 in the UMR. Comparisons of the spatial distribution of the prevalence rates for allergic rhinitis and annual average pollutant concentrations over the region showed that a relatively high prevalence rate occurred around the coastal industrial area, with high PM10 concentrations. A linear correlation analysis demonstrated a positive correlation relationship between them (R = 0.680, p = 0.04). Multiple linear regression analysis revealed that the combined effect of the PM10 and $SO_2$ variables accounts for approximately 81% of the variance (R-square: 0.81) in the prevalence rate. From the multiple logistic regression analysis after adjustment by age, sex, and air-pollutant factors, the PM10 and $SO_2$ which were mainly from industrialrelated emissions were found to be significantly associated with an increased risk of allergic rhinitis (aOR: 1.76, 95% CI: 1.15-2.70 for PM10 ; aOR: 1.63, 95% CI: 1.12-2.35 for SO2).

• Korean Journal of Health Education and Promotion
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• v.26 no.1
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• pp.93-104
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• 2009

Objectives: Although Asian immigrants have lower rates of smoking and binge drinking than other ethnics in the US, Korean Americans have the highest rate of Asian immigrants. This study, therefore, compared with the rates and examined the predictors of smoking and binge drinking by gender and ethnicity among Asian immigrants in California. Methods: In 2001 and 2003, California Health Interview Survey (CHIS) were conducted in English and their original languages with Asian immigrants residing in 58 Counties and 3 Cities, California. We performed analysis to find out the differences of smoking and binge drinking rates using the secondary data, CHIS 2001 and 2003. Multiple logistic regression analysis for survey data identified predictors of smoking and binge drinking behaviors by gender and ethnicity. Results: Korean American males (35.4%) and Japanese American females (15.4%) had higher rates of smoking prevalence compared with other Asian immigrants in California. In binge drinking, 26.5% of male and 8.1% of female among Korean Americans were binge drinker, and the rates were the top with Asian Americans who had lived in California. It showed the remarkable gap between gender of smoking and binge drinking among Vietnamese immigrants, whereas not the striking difference among Japanese Americans. In multiple regression models, age, educational level, occupation, marital status, English proficiency, and health insurance coverage remained significant for smoking and binge drinking behaviors(P<0.05). Even though the time in the US was not significant, it seemed to be related to educational level and English proficiency. In particular among female, smoking and binge drinking behaviors were associated with acculturation. Conclusion: Although Asian Americans had shared with American culture since they had immigrated in the US, they had significantly different prevalence rates of smoking and binge drinking based on gender and ethnicity. Therefore, future efforts should be focused on understanding differences by ethnicity and target at high-risk subgroups. To achieve this, it needs to develop the educational materials in Korean and their original languages.

• Safety and Health at Work
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• v.8 no.2
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• pp.162-168
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• 2017

Background: Pelvic ring fractures (PRFs) may influence the daily activities and quality of life of the injured. The aim of this retrospective study was to explore the functional outcomes and factors related to return to work (RTW) after PRF. Methods: During the years 2003-2012, 282 injured individuals aged 20-55 years on the date of the accident, were hospitalized and treated for PRFs in a large tertiary hospital in Athens, Greece. One hundred and three patients were traced and contacted; 77 who were on paid employment prior to the accident gave their informed consent to participate in the survey, which was conducted in early 2015 through telephone interviews. The questionnaire included variables related to injury, treatment and activities, and the Majeed pelvic score. Univariate and multiple regression analyses were used for statistical assessment. Results: Almost half of the injured (46.7%) fully RTW, and earning losses were reported to be 35% after PRF. The univariate analysis confirmed that RTW was significantly related to accident site (labor or not), the magnitude of the accident's force, concomitant injuries, duration of hospitalization, time to RTW, engagement to the same sport, Majeed score, and complications such as limp and pain as well as urologic and sexual complaints (p < 0.05 for all). On multiple logistic regression analysis, the accident sustained out of work (odds ratio: 6.472, 95% confidence interval: 1.626-25.769) and Majeed score (odds ratio: 3.749, 95% confidence interval: 2.092-6.720) were identified as independent predictive factors of full RTW. Conclusion: PRFs have severe socioeconomic consequences. Possible predictors of RTW should be taken into account for health management and policies.