• Quality Improvement in Health Care
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• v.24 no.2
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• pp.41-61
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• 2018

Purpose: Falls are one of the most frequent health events in medical institutions, however, they can be predicted and prevented. The Quality Improvement Nurse Society clinical practice guideline Steering Committee developed the Clinical Practice Guideline for the assessment and prevention of falls in adult people. The purpose of this study was to assess the risk factors for falls in adults aged 19 years and older, to present an evidence for preventing falls, formulate a recommendations, and indicators for applying the recommendations. Methods: This clinical practice guideline was developed using a 23-step adaptation method according to the Handbook for clinical practice guideline developer (version 1.0) by National Evidence-based Healthcare Collaborating Agency. Evidence levels and recommendation ratings were established in accordance to SIGN 2011 (The Scottish Intercollegiate Guidelines Network). Results: The final 15 recommendations from four domains were derived from experts' advice; 1) assessment of risk factor for falls in adult 2) preventing falls and reducing the risks of falls or falls-related injury 3) management and reassessment after a person falls 4) leadership and culture. Conclusion: This clinical practice guideline can be used as a basis for evaluation and prevention of fall risk factors for adults, to formulate recommendations for fall risk assessment and fall prevention, and to present monitoring indicators for applying the recommendations.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.2
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• pp.147-155
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• 2021

Objective: The purpose of this study was to find ways for strengthening occupational health services through monitoring exposure to health hazards. Methods: About 70,000 workplaces that have conducted the work environment measurement(WEM) over the last three years(2017~2019) were classified according to the Korean Standard Industry Classification(KSIC), and the current status of WEM by industry was analyzed. The authors considered ways to monitor exposure to health hazards in order to strengthen occupational health services and protect workers' health. Results: Based on the KSIC, 934 of the 1,196 total sub-classified industries have conducted WEM in at least one workplace over the last three year(2017~2019). In the case of manufacturing, out of a total of 477 sub-classified industries, 474 have conducted WEM at more than one workplace. However, in some industries, WEM was not conducted or the implementation rate was low, so it was necessary to examine whether WEM should be expanded based on a detailed analysis of the WEM database. To this end, it is necessary to form an exposure monitoring committee in which various experts from different fields can participate. The committee needs to discuss the overall matters necessary for selecting industries that require detailed investigation or research, review the results, and prepare a final recommendation. Conclusion: In conclusion, the government needs to come up with a plan to strengthen occupational health services through surveys and research on the current status of WEM and work environment management models by industry.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.85-91
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• 2021

This study is a methodological study that explains the procedure for verifying effectiveness in developing practical guidelines for cognitive programs suitable for dementia patients. Based on the development of evidence-based new clinical practice guidelines, a preliminary recommendation for the domestic dementia patient care guidelines was developed. The practical guidelines consisted of the final four types, and the content validity score of the configuration items was 0.87 to 1 point. In the sub-categories of field applicability, appropriateness score was 3.95 to 4.34 points, applicability score was 3.57 to 4.27 points, and predicted effect score was 3.84 to 4.22 points. Through the examination of the content validity and field applicability of experts, it was confirmed that the practical guidelines developed in this study can be used as the basis for establishing an intervention plan for dementia cognitive program managers engaged in clinical practice. In future studies should further facilitate the development of evidence-based treatment guidelines to select appropriate treatment activities for dementia patients.

• The Korea Journal of Herbology
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• v.33 no.1
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• pp.9-15
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• 2018

Objectives : The root bark of Dictamnus dasycarpus has been frequently used to treat patients with skin diseases in Korea. Recently, wild root of D. dasycarpus are reported to induce liver injury. Methods : Traditional uses of D. dasycarpus for skin diseases were analysed bibliographically. In addition, reported cases were collected and analysed using pubmed and national digital library. Results : In taiwan, D. dasycarpus revealed to be one of major herbs for skin diseases and many researchers in worldwide had reported its dermatological efficacies. Reported cases related in liver injury described that hepatocellular or cholestatic liver injury were seen in patients eating wild root of D. dasycarpus. In addition, 6 cases in worldwide and 1 case in Korea showed that patients with drug induced liver injury (DILI) ingested not root bark of D. dasycarpus but prescriptions containing root bark of D. dasycarpus. These mean that wild root of D. dasycarpus (Bongsam or Bongwhangsam) was estimated to be closely related in DILI. Whereas, it was difficult to confirm direct correlation between root bark of D. dasycarpus used as herbal medicine by doctor of Korean medicine and DILI. Conclusions : these results imply that wild root of D. dasycarpus is closely related in DILI and strong recommendation not to take it without consultation by experts is needed. In addition, although there are no evidences of direct correlation between root bark of D. dasycarpus and DILI, doctor of Korean medicines should pay attention to use root bark of D. dasycarpus in their clinics.

• Asian Oncology Nursing
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• v.5 no.1
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• pp.11-21
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• 2005

The purpose of this study were to develop an web-based education program for Lung cancer patients and to test its effects on patients' self-care knowledge, compliance to medical regimen, nutrition status and pain. The program was developed by the following process: first, Lung cancer patients demand on the web-based program was investigated. and second, the program was developed with the help of various reference books and then validation of experts group. last, educations effects on the patients is evaluated and compared the differences in self-care knowledge, compliance to medical regimen, nutrition status and pain between on experimental group and a control group on before discharge 1day and 3weeks after. SPSS/Win 11.0 program was used for data analysis. It was proven with $x^2$ test and t-test, and Pearson Correlation coefficient, and Chronbach's alpha coefficient were done for the reliability of measuring instruments. 1. The summary of the Program development is as follows. The program is based on patients' questionnaire and reference material and is made for users friendly. Not only Bigger font size and bright colors but also illustrations or pictures were adopted to help enhance patients' understanding. 2. The summary of the study results is as follows. 1) Compared with control group, the web-based educated experimental group showed a statistical significant difference on self-care knowledge, Especially disease, radiation treatment, medication & analgesics, chemotherapy side effect, but there was no significant difference in the field of chemotherapy, in the fields of operation, diet & general knowledge. 2) Compared with control group, the web-based educated experimental group showed a statistical significant difference on compliance to medical regimen, especially in the field of follow up care, everyday life, diet, but there was no significant difference in the field of medication, exercise. 3) Compared with control group, web-based educated experimental group showed no significant difference in nutrition status, but partially significant difference in body weight. 4) Compared with control group, the web-based educated experimental group showed no significant difference in pain level. 5) The significantly positive correalation self-care knowledge with the compliance to medical regimen. 6) Users satisfaction with the web-based education program of the contents quality, the level of recommendation to others, content layout, medical information quality, but interesting got a low mark.

• Journal of Environmental Impact Assessment
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• v.27 no.3
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• pp.241-250
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• 2018

Recently, negative effects on human health such as disease caused by harmful environment have been dealt with seriously. In particular, studies on the effect of radon exposure, which is known as a primary carcinogen in lung cancer due to radioactive materials, have been actively studied. In Korea, since January 1, 2018, radon measurement is mandatory when building a new apartment, so it is necessary to measure the radon concentration and submit it to the local government and it should be posted where residents can see it. Radon has only recommended standards for multi-use facilities, but now it has decided to set recommendation standards for private homes. Therefore, it should now be possible to manage the radon in the environmental impact assessment phase as well as in the Post-environmental Impact Assessment. It should be possible to share health information such as the radon concentration and the risk of radon, and participation of health experts in the environmental impact assessment stage is required. Soil, air quality, hygiene and aerial items should be improved to take into account the effects of radon on human health during the environmental impact assessment process. If the level value of conncentration of radon shows above the recommended level, then alternative measures should be prepared and mitigation measures should be prepared as well.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.188-195
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• 2016

This study is a cross sectional, descriptive research that utilized the Korean version of the BHCC (Behavior Health Care Competency) measurement tools to compare and contrast the BHCC level between nurses stationed in psychiatric and general ward departments. The research subjects were selected from 6 hospitals that have at least 300 beds located in Seoul city and Gyeonggi Province. There were a total of 190 nurses, consisting of 90 nurses from the psychiatric ward department and 100 nurses from the general ward department. The comparison demonstrated that nurses from psychiatric ward department showed a higher BHCC compared to general department nurses in most items. In the case of psychiatric ward nurses, compared to general ward nurses, the assessment was 5.29 times higher, the intervention was 6.06 times higher and the proper use of resources was 2.63 times higher. On the other hand, the treatment recommendation had no influence. Accordingly, education and training for general ward nurses should be improved and hospital administrators should pay more attention in conducting the BHCC education for the general ward nurses and on fostering education experts to develop related programs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.527-535
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• 2021

Traditional business intelligence (BI) systems have been used widely as tools for better decision-making on time. On the other hand, building a data warehouse (DW) for the efficient analysis of rapidly growing data is time-consuming and complex. In particular, the ETL (Extract, Transform, and Load) process required to build a data warehouse has become much more complex as the BI platform moves to a cloud environment. Various BI solutions based on the NoSQL database, such as MongoDB, have been proposed to overcome these ETL issues. Decision-makers want easy access to data without the help of IT departments or BI experts. Recently, self-service BI (SSBI) has emerged as a way to solve these BI issues. This paper proposes a self-service BI system with farming data using the MongoDB cloud as DW to support the selection of new crops by return-farmers. The proposed system includes functions to provide insights to decision-makers, including data visualization using MongoDB charts, reporting for advanced data search, and monitoring for real-time data analysis. Decision makers can access data directly in various ways and can analyze data in a self-service method using the functions of the proposed system.

• Management & Information Systems Review
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• v.39 no.3
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• pp.1-16
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• 2020

The current tariff return system requires tax officials to calculate tax amount by themselves and pay the tax amount on their own responsibility. In other words, in principle, the duty and responsibility of reporting payment system are imposed only on the taxee who is required to calculate and pay the tax accurately. In case the tax payment system fails to fulfill the duty and responsibility, the additional tax is imposed on the taxee by collecting the tax shortfall and imposing the tax deduction on For this reason, item classifications, together with tariff assessments, are the most difficult and could pose a significant risk to entities if they are misclassified. For this reason, import reports are consigned to customs officials, who are customs experts, while paying a substantial fee. The purpose of this study is to classify HS items to be reported upon import declaration and to indicate HS codes to be recorded on import declaration. HS items were classified using the attached image in the case of item classification based on the case of the classification of items by the Korea Customs Service for classification of HS items. For image classification, CNN was used as a deep learning algorithm commonly used for image recognition and Vgg16, Vgg19, ResNet50 and Inception-V3 models were used among CNN models. To improve classification accuracy, two datasets were created. Dataset1 selected five types with the most HS code images, and Dataset2 was tested by dividing them into five types with 87 Chapter, the most among HS code 2 units. The classification accuracy was highest when HS item classification was performed by learning with dual database2, the corresponding model was Inception-V3, and the ResNet50 had the lowest classification accuracy. The study identified the possibility of HS item classification based on the first item image registered in the item classification determination case, and the second point of this study is that HS item classification, which has not been attempted before, was attempted through the CNN model.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.