• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.163-170
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• 2020

With the development of information and communication technologies, the growing volume of data is increasing exponentially, raising interest in big data. As technologies related to big data have developed, big data is being collected, stored, processed, analyzed, and utilized in many fields. Big data analytics in the health care sector, in particular, is receiving much attention because they can also have a huge social and economic impact. It is predicted that it will be able to use Big Data technology to analyze patients' diagnostic data and reduce the amount of money that is spent on simple hospital care. Therefore, in this thesis, patient data is analyzed to present to patients who are unable to go to the hospital or caregivers who do not have medical expertise with close care guidelines. First, the collected patient data is stored in HDFS and the data is processed and classified using R, a big data processing and analysis tool, in the Hadoop environment. Visualize to a web server using R Shiny, which is used to implement various functions of R on the web.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.341-347
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• 2014

Among methods of the big data process, big data process under the cloud environment is becoming a main topic. As part of solving faced problem and strengthening industrial competitiveness in the medical and health industry, discussion on ways to activate big data is actively being conducted. Because the reason is a paradigm shift, saving pressure for increasing health care costs, and increased consumer interest for the level of service. In this paper, we find out the relationship between the cloud and big data. And we are to research and analysis a cloud-based big data case in the medical field. Finally we propose the efficient utilization and future outlook. For the smooth functioning of cloud-based medical big data, we have to solve the problems like infrastructure extension, analysis/application software development, and professional manpower training. In addition, we have to correct insufficient laws maintenance to the Cloud utilization, and improve the security and the recognition to personal information, and solve authority for data centralization.

• Journal of Preventive Medicine and Public Health
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• v.26 no.4 s.44
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• pp.661-671
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• 1993

In order to compare the geographical distribution of physician by level of medical care and specialty, a log linear model was applied to the annual registration data of the Korean Medical Association as of the end of December, 1991 which was supplemented from related institutions and adjusted with relevant sources. Those physicians in primary and secondary care institutions were not statistically significantly unevenly distributed by province-level catchment area. There were some differences in physician distribution among big cities, medium and small-sized cities, and counties; however, those physicians for primary care level were equitably distributed between cities and counties. Specialties for secondary care physicians were less evenly distributed in county areas than in city areas, and generalists are distributed more evenly in cities and counties than in big cities. There is a certain limitation due to underregistration in the annual physician registration to the Korean Medical Association; however, the geographical distribution of physicians has been improved quantitatively. It is strongly suggested that specialties and the level of medical care should be considered for further physician manpower studies.

• Journal of Preventive Medicine and Public Health
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• v.50 no.1
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• pp.29-37
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• 2017

Objectives: The accurate measurement of geographic patterns of health care utilization is a prerequisite for the study of geographic variations in health care utilization. While several measures have been developed to measure how accurately geographic units reflect the health care utilization patterns of residents, they have been only applied to hospitalization and need further evaluation. This study aimed to evaluate geographic indices describing health care utilization. Methods: We measured the utilization rate and four health care utilization indices (localization index, outflow index, inflow index, and net patient flow) for eight major procedures (coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, surgery after hip fracture, knee replacement surgery, caesarean sections, hysterectomy, computed tomography scans, and magnetic resonance imaging scans) according to three levels of geographic units in Korea. Data were obtained from the National Health Insurance database in Korea. We evaluated the associations among the health care utilization indices and the utilization rates. Results: In higher-level geographic units, the localization index tended to be high, while the inflow index and outflow index were lower. The indices showed different patterns depending on the procedure. A strong negative correlation between the localization index and the outflow index was observed for all procedures. Net patient flow showed a moderate positive correlation with the localization index and the inflow index. Conclusions: Health care utilization indices can be used as a proxy to describe the utilization pattern of a procedure in a geographic unit.

• The Journal of Industrial Distribution & Business
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• v.13 no.11
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• pp.1-10
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• 2022

Purpose: This study measures the influence of facilitating conditions on employees' attitudes towards the adoption of big data analytics by selected medical aid organizations in Durban. In the health care sector, there are various sources of big data such as patients' medical records, medical examination results, and pharmacy prescriptions. Several organizations take the benefits of big data to improve their performance and productivity. Research design, data, and methodology: A survey research strategy was conducted on some selected medical aid organizations. A non-probability sampling and the purposive sampling technique were adopted in this study. The collected data was analysed using version 23 of Statistical Package for Social Science (SPSS) Results: the results show that the "facilitating conditions" have a positive influence on employees' attitudes in the adoption of big data analytics Conclusions: The findings of this study provide empirical and scientific contributions of the facilitating conditions issues regarding employee attitudes toward big data analytics adoption. The findings of this study will add to the body of knowledge in this field and raise awareness, which will spur further research, particularly in developing countries.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.973-980
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• 2020

Various applied solutions utilizing the technology of the 4th Industrial Revolution are being applied to the health and welfare sector. In the proposed paper, the senior care system solution based on big data is designed. The principles of operation of the proposed system are collecting senior behavioral analyses through API information of smart devices, and sending a primary notification to the relevant senior in cases where a senior reacts differently from the existing standards. A system is proposed to prevent dangerous situations by providing information to peer seniors, family members, and the emergency center in cases where there is no response.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.238-243
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• 2019

Recently, the importance of big data continues to be emphasized, and it is applied in various fields based on data mining techniques, which has a great influence on the health care industry. There are many healthcare industries, but only home health care is considered here. However, applying this to real problems does not always give perfect results, which is a problem. Therefore, data mining techniques are used to solve these problems, and the algorithms that affect performance are evaluated. This paper focuses on the effects of healthcare services on patient satisfaction and satisfaction. In order to use the CVParameterSelectin algorithm and the SMOreg algorithm of the classify method of data mining, it was evaluated based on the experiment and the verification of the results. In this paper, we analyzed the services of home health care institutions and the patient satisfaction analysis based on the name, address, service provided by the institution, mood of the patients, etc. In particular, we evaluated the results based on the results of cross validation using these two algorithms. However, the existence of variables that affect the outcome does not give a perfect result. We used the cluster analysis method of weka system to conduct the research of this paper.

• Korea Journal of Hospital Management
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• v.27 no.1
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• pp.1-10
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• 2022

Background: This study aims to empirically compare and evaluate the current status of medical accessibility and health inequality between people with disabilities and without. We calculated the ACSC hospitalization rate, which is a medical accessibility index, for hypertension, a major risk factor for cardiovascular disease that accounts for more than 20% of deaths among people with disabilities using the 2016 National Health Insurance Big Data. Methods: The subjects of the study were a total of 601,520, including 64,018 people with disabilities and 537,501 people without. Logistic regression was performed to analyze the differences in hypertension hospitalization rates adjusted for demographic and sociological characteristics and disease characteristics using SAS 9.4 program. Results: Before adjusting for the characteristics, the hypertension hospitalization rate of people with disabilities was 1.55%, and the people without disabilities were 0.49%. After adjusting, it was found that people with disabilities were 2.11 times higher than people without disabilities, and it was statistically significant. Conclusion: The preventable hospitalization rate of people with disabilities is higher than that of people without, suggesting that the disabled have problems with access to medical care and health inequality. Therefore, the government's policy improvement is required to close the medical gap for the disabled.

• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.17-23
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• 2015

Due to the development of information and communication technology as health care service is popular variety utilizing bioinformatics patient information services are being provided to the patient. In particular, the healthcare utilizing bioinformatics information, and change in a variety of healthcare trends. However, healthcare services using bioinformatics information of the patient and the complexity of the disease, new diseases (SARS, AIDS, etc .) due to the emergence of increasing health care costs and health promotion services provided to patients may not be smooth. In this paper, we propose a model for low-cost health services and medical care of patients bioinformatics fast access to information. The proposed model can be so big a bioinformatics data formation by the patient's patient information anytime / anywhere providing medical services in the home or the nearest hospital for their own disease management. In particular, the proposed model of health care services is characterized improve work efficiency, reducing the burden on hospitals by passing a medical illness to easily analyze patient information.