• Journal of Preventive Medicine and Public Health
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• v.22 no.4 s.28
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• pp.555-577
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• 1989

This study was conducted to compare the delivery management including laboratory tests, medication and surgical procedures for the delivery in various medical facilities. Two university hospitals, two general hospitals, three hospitals, two private obstetric clinics, and two midwifery clinics in a large city were selected as they permitted the investigators to abstract the required data from the medical and accounting records. The total number of deliveries occurred at these 11 facilities between 15 January and 15 February, 1989 was 789 among which 606(76.8%) were vaginal deliveries and 183 (23.3%) were C-sections. For the normal vaginal deliveries, CBC, Hb/Hct level, blood typing, VDRL, hepatitis B antigen and antibody, and urinalysis were routinely done except the private clinics and midwifery clinics which did not test for hepatitis B and Hb/Hct level at all. In one university hospital ultrasonography was performed in 71.4% of the mothers and in one general hospital liver function test was done in 76.7% of the mothers. For the C-section, chest X-ray, bleeding/clotting time and liver function test were routinely done in addition to the routine tests for the normal vaginal deliveries. Episiotomy was performed in 97.2% of the vaginal deliveries. The type and duration of fluid infused and antibiotics administered showed a wide variation among the medical facilities. In one university hospital antibiotics was not administered after C-section at all while in the general hospitals and hospitals one or two antibiotics were administered for one week on the average. In one private clinic one pint of whole blood was transfused routinely. A wide variation was observed among the medical facilities in the use of vitamin, hemostatics, oxytocics, antipyreptics, analgesics, anti-inflammatory agents. sedatives. digestives. stool softeners. antihistamines. and diuretics. Mean hospital day for the normal vaginal deliveries of primipara was 2.6 days with little variation except one hospital with 3.5 days. Mean hospital day for the C-section of primipara was 7.5 days and that of multipara was 7.6 days and it ranged between 6.5 days and 9.4 days. Average hospital fee for a normal vaginal delivery without the medical insurance coverage was 182,100 Won for the primipara and 167,300 Won for the multipara. In case of the primipara covered by the medical insurance a mother paid 82,400 Won and a multiparous mother paid 75,600 Won. Average hospital fee for a C-section without the medical insurance was 946,500 Won for the primipara and 753,800 Won for the multipara. In case of the primipara covered by the medical insurance a mother paid 256,200 Won and a multiparous mother paid 253,700 Won. Average hospital fee for a normal vaginal delivery in the university hospitals showed a remarkable difference, 268,000 Won vs 350,000 Won, as well as for the C-section. A wide variation in the laboratory tests performed for a normal vaginal delivery and a C-section as well as in the medication and hospital days brought about a big difference in the hospital fee and some hospitals were practicing the case payment system. Thus, standardization of the medical care to a certain level is warranted for the provision of adequate medical care for delivery.

• Journal of Korean Public Health Nursing
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• v.7 no.1
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• pp.31-48
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• 1993

Nowaday, there have a lot of changes in the demands of the aged persons. Their problems also came to the fore with diverse forms under the influences of industrialization, urbanization and nuclear family. To make the matter worse, the aged population is mounting rapidly. Also, such structure as nuclear family is widely disseminating uncomfortable to the aged. People is mainly being guided by self interest above everything else. Indeed, they had, all together, bad effects on our traditional value system regarding 'respect for the aged and devotion to patients'. It seems unfortunately obvious that the family responsibility is gradually weakening to support the old who is a dependent family. The result is that the aged must have suffered all sorts of hardships in lightenning psychological, physical and economical difficulties. First, to grasp the situations and conditions supporting for single aged persons from each view of psychological, emotional, family-relational, healthy, social and economical standpoints, and second, to analyze their own recognition levels thinking of their health conditions and the relationships between the supporting environments of old family dependants and their psychological healths and then finally, to propose suggestions being able to be helpful for living comfortably in an old age and thereby, building up good family relation. The statistical techniques used to analyze 115 respondents living in Puchun city are frequency, $x^2$ test, t-Jest, ANOVA, Pearson's Correlation Coefficiency and Regression analysis (SPSS package), pertnent to prove the hypothesis suggested in this paper. Of course, it is needless to say that more data are needed on this point. However, several main research findings can be summarized as follows: First, the better single aged persons may be in the habit of eating a meal and the higher they may think of their physical health conditions and movement, the more they want to participate in economic activities to be free from economical dependence upon their children and to overcome lonliness. Second, single aged women appear to have had higher ability to take care their health for themself than single aged men do. It is why signle aged women do not, in general, have big problems to manage their health. But, as shown in this paper, single aged person"s were more liable to the diseases of the aged and, thereby, requiring special medical treatment badly to be healthy. Third. single aged persons revealed potential desires to free themself from socio economic dependence upon their children even in simple labor Job which can draw a monthly salary of about W200, 000. Fourth, they are generally satisfied with their children's filial piety toward them. Nonethless, most of them appear to be reluctantly dependent upon their children and live lonly lives very much. Fifth, they seem to have some hesitation in expressing their candid opinions as that then are some others along with family environmental factors for psychological and emotiona stability. Accordingly, it is safe to conclude by saying that much attention should' be paid no only to socio-economic supports and better medical services for the aged but also to political supports of the society and towards their children for the aged's emotiona support, for improving the quality of their lives in old age and promoting efficiency in suporting for old family dependants.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.699-706
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• 2009

The convergence tendency accelerates the realization of the ubiquitous healthcare (u-Healthcare) between the technology including the power generaation and IT-BT-NT of the ubiquitous computing technology. By rapidly analyzing a large amount of collected from the sensor network with processing and delivering to the medical team an u-Healthcare can provide a patient for an inappropriate regardless of the time and place. As to the existing u-Healthcare, since the sensor node all transmitted collected data by using with the Zigbee protocol the processing burden of the base node was big and there was many communication frequency of the sensor node. In this paper, the u-Healthcare system in which it can efficiently apply to mobile apparatuses it provided the transfer rate in which it is superior to the bio-signal delivery where there are the life and direct relation which by using the Bluetooth instead of the Zigbee protocol and in which it is variously used in the ubiquitous environment was designed. Moreover, by applying the EEF(Embedded Event Filtering) technique in which data in which it includes in the event defined in advance selected and it transmits with the base node, the communication frequency and were reduced. We confirmed to be the system in which it is efficient through the simulation result than the existing Electrocardiogram Measurement system.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.227-233
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• 2015

The recent health care is growing rapidly want to receive offers users a variety of medical services, can be exploited easily exposed to a third party information on the role of the patient's hospital staff (doctors, nurses, pharmacists, etc.) depending on the patient clearly may have to be classified. In this paper, in order to ensure safe use by third parties in the health care environment, classify the attributes of patient information and patient privacy protection technique using hierarchical multi-property rights proposed to classify information according to the role of patient hospital officials The. Hospital patients and to prevent the proposed method is represented by a mathematical model, the information (the data consumer, time, sensor, an object, duty, and the delegation circumstances, and so on) the privacy attribute of a patient from being exploited illegally patient information from a third party the prevention of the leakage of the privacy information of the patient in synchronization with the attribute information between the parties.

• Korea Journal of Hospital Management
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• v.2 no.1
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• pp.162-182
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• 1997

This study was carried out to assess the current status of hospital wage structure and to find out the characteristics and problems in the current hospital wage structure. so as to provide empirical data for establishing a rational wage structure. The data were collected from administrative personnels in charge of wage management in 31 hospitals by using a structured questionnaire through direct visiting and mailing in Pusan Metropolitan City. The major findings in this study were as follows: First, the hospital wage structure applied differently to the basic wages between doctors and the other employees. The wage structure for doctors included performance rate of 51.6%, followed by a synthesis rate of 29.0%, while the wage for the other employees had the synthesis rate of 74.2%, followed by the seniority rate of 12.9%. Second, the wage consisted of a basic wage for 57.5%. the allowance for 21.1% and monthly installed bonus for 21.4%, and the basic wage comprised 68.3% of the total wage for doctors, as compared to 51.9% for nurses and medical technicians and 52.4% for administrative and managerial personnel. The annual rate of the bonus was average 460%, and 96.8% of the hospital did not consider personnel preformance appraisal when paying the bonus. Third, 80.6% of the hospitals applied the legal rate to the retirement allowance while 19.4% applying cumulative rates more than the legal rate, and all of university hospitals applied cumulative rates. Retirement reserves were practiced only in 54.9% of the hospitals. Forth, many hospitals seemed to be interested in applying graded wage system according to performance, by showing that 42.9% of the hospitals were planning to apply it in the future, despite only 9.7% practicing it. Fifth, the wage structure appeared to be complicated due to various kinds of allowances. The kind of the allowances varied among hospitals, ranging from 2 to 26 kinds, and increased as the size of hospital was larger. Sixth, the opinions leading to improve the basic wage structure favored the seniority rate for 51.6% either to maintain the present seniority rate(16.1%) or to apply the incentive pay in addition to the senior rate(35.5%). and also favored the performance rate for 35.5%, followed by the job rate for 12.9%. In conclusion, the current hospital wage structure seemed to be too complicated to reflect personal ability, contribution and performance and to become a big barrier to inducing worker's motivation and to strengthening in competitveness. Therefore it is suggested that the current wage structure should be revised to the one emphasizing on job and ability base with considering characteristics and situation of the hospital, rather than seniority factors.

• Journal of radiological science and technology
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• v.38 no.4
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• pp.375-381
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• 2015

Digital Radiography is a big part of diagnostic radiology. Because uncorrected digital radiography image supported false effect of Patient's health care. We must be manage the correct digital radiography image. Thus, the artifact images can have effect to make a wrong diagnosis. We report types of occurrence by analyzing the artifacts that occurs in digital radiography system. We had collected the artifacts occurred in digital radiography system of general hospital from 2007 to 2014. The collected data had analyzed and then had categorize as the occurred causes. The artifacts could be categorized by hardware artifacts, software artifacts, operating errors, system artifacts, and others. Hardware artifact from a Ghost artifact that is caused by lag effect occurred most frequently. The others cases are the artifacts caused by RF noise and foreign body in equipments. Software artifacts are many different types of reasons. The uncorrected processing artifacts and the image processing error artifacts occurred most frequently. Exposure data recognize (EDR) error artifacts, the processing error of commissural line, and etc., the software artifacts were caused by various reasons. Operating artifacts were caused when the user didn't have the full understanding of the digital medical image system. System artifacts had appeared the error due to DICOM header information and the compression algorithm. The obvious artifacts should be re-examined, and it could result in increasing the exposure dose of the patient. The unclear artifact leads to a wrong diagnosis and added examination. The ability to correctly determine artifact are required. We have to reduce the artifact occurrences by understanding its characteristic and providing sustainable education as well as the maintenance of the equipments.

• Research in Community and Public Health Nursing
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• v.11 no.2
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• pp.399-410
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• 2000

In this, analyzing the type of subjectivity in which people would have about home visit nursing services originating from public health care centers. I tried to research more effective ways to improve home visit nursing care services. and later. for the development of home visit nursing care. to supply basic data. The method for this study was the Q-method. created by William Stephenson. and was adequate for the study of subjectivity. For this study. through the deep interview. literature inquiry, and the discussion course. 206 Q-statement sentences were abstracted. and based on them, after Q-sample-selection. I then collected the Q-categorized-result from 32 subjects from Mar. 10. 2000 to Mar. 25. 2000. Through the statistic a analysis of PC-Qunal program. the subjectivity species were categorized and analyzed. The study results show that there are 3 sorts of recognition types. and they are analyzed in the following; The first type: the positively receiving type shows that they feel thankful and a trusting feeling about home visit nursing. The second type: the negatively mistrusting type shows that they had doubtful attitudes about the specialty of home visit nursing: they wanted medicine or nutrition remedies rather than health education and concerning the their own health care, they prefered the hospitals or clinics. The third type: the conditional receiving type shows that even though they had a positive receiving attitude about home visit nursing wanting to consult with the home visit nurses about the difficult problem which could not easily be settled, hoping that the home visit nurses could visit them more often, in their actual lives. they strongly indicated their attitudes concerning money as more important than home visits. The subjects in these 3 types commonly had a good feeling about the kindness of the home visit nurses: the first and third types also had a positive recognition about home visit nursing; however. in aspects of the evaluation and receiving attitudes, they showed a big difference. When all the above results are integrated. in the case of the first type the home visit nursing service, which satisfied the demand for health care of the medically weak people. should be continuously supplied. Additionally in case of the second type (negatively mistrust). continuous education and support should be supplied with enough interest to lead their concerns about their own health care as well as lead medical spending in a productive and effective direction in order to change their impressions. Through this study. I learned that the recognition of the objectives of home visit nursing services can be categorized in to 3 types and could be analyzed. Thus I wish that this study helps to present basic data which contributes to the development of the home visit nursing field.

• Journal of vocational education research
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• v.37 no.1
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• pp.101-118
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• 2018

The purpose of this study was to investigate the effect size of the difference of job satisfaction by type of employment by combining data from previous studies. For this purpose, the total of 95 articles analyzed. For the analysis of data, CMA(Comprehensive Meta-Analysis) 2.0 program was used and statistical significance was set at 5%(${\alpha}=0.05$). The main conclusions of this study are as follows. First, regular workers have higher job satisfaction than non-regular workers and the effect size of employment type is medium. Second, among five constituents of job satisfaction, the difference of wage and promotion satisfaction is greater than the difference of satisfaction in human relations, work and working environment satisfaction. Third, the job satisfaction of regular and non-regular workers differs according to the occupation areas. Fourth, there is a big difference in job satisfaction in financial, insurance, food and service occupation areas, and regular workers have higher job satisfaction than non - regular workers. On the other hand, non-regular workers have higher job satisfaction than regular workers in health, medical, social occupation areas.