• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.149-160
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• 2021

One of the most important inventions and developments in the digital world today is the healthcare system based on blockchain technology. Healthcare is an important field that requires the application of security mechanisms due to the sensitivity of patient data. The association of blockchain with healthcare contributed to achieving better security mechanisms than the traditional approach. The new approach operates in a decentralized system, which in turn, improves security in the healthcare environment. Consequently, blockchain technology has emerged as one of the most crucial solutions to security violations and challenges in the healthcare industry. This paper provides a comprehensive review of several experts' recent protection and detection approaches in this domain. It is also imperative to note that the paper focuses only on the recent techniques that have been published during 2017-2020. The sophisticated procedures have been investigated and discussed in terms of similarities and differences to highlight the significance of the protection needed to secure the healthcare environment.

• Health Policy and Management
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• v.11 no.3
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• pp.102-120
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• 2001

This paper examines the current situation and major impacts of e-business on healthcare industry: hospital, pharmaceutical, medical device and health-related internet sectors. Of the 137 samples collected with mail survey, the utilization rate of B2C e-commerce is 31.4% and B2B is 13.1%. And 74.5% of respondents remains the first development stage which represents the simple advertisement such as the one-way information offering. The key obstacle of expansion of health care e-commerce turns out to be the illogical and outdated medical-related law and institution. Finally, policy recommendations are proposed based on the evaluation of the current policy implemented by government.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.75-82
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• 2020

It is important to secure patient healthcare information in medical institutions. Education can enhance healthcare information security practice. The purpose of this study is to investigate the effect size of the correlation between healthcare information security education and healthcare information security practice in medical institutions. Systematic Review and Meta-Analysis were used for this study. Data were collected from January 1, 2010 to July 31, 2019 through DBpia, RISS, NDSL. Four studies were eligible for inclusion in the analysis. Data were analyzed with R. The results of the Meta-Analysis demonstrated statistically significant large effect size of correlation with education and practice. Based on the results of this study, we will be able to understand the importance of healthcare information security education in medical institutions and use them as a basis for developing healthcare information security education programs.

• The Journal of Information Systems
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• v.30 no.3
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• pp.21-45
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• 2021

Purpose This paper analyzed the impacts of domestic stock market by a global pandemic such as COVID-19. We investigated how the overall pattern of the stock market changed due to the impact of the COVID-19 pandemic. In particular, we analyzed in depth the pattern of stock price, as well, tried to find what factors affect on stock market index(KOSPI) in the healthcare industry due to the COVID-19 pandemic. Design/methodology/approach We built a data warehouse from the databases in various industrial and economic fields to analyze the changes in the KOSPI due to COVID-19, particularly, the changes in the healthcare industry centered on bio-medicine. We collected daily stock price data of the KOSPI centered on the KOSPI-200 about two years before and one year after the outbreak of COVID-19. In addition, we also collected various news related to COVID-19 from the stock market by applying text mining techniques. We designed four experimental data sets to develop decision tree-based prediction models. Findings All prediction models from the four data sets showed the significant predictive power with explainable decision tree models. In addition, we derived significant 10 to 14 decision rules for each prediction model. The experimental results showed that the decision rules were enough to explain the domestic healthcare stock market patterns for before and after COVID-19.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.175-182
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• 2021

The purpose of this study is to establish the direction of industrial policy by comparing the employment inducement effect on the related industries of the digital bio-healthcare industry. The analysis data used the three-year input-output table measured by the Bank of Korea. First, the research method was rewritten into 7 major industries to compare statistical data by period. Second, the Bank of Korea's industry-related analysis methodology was utilized. Third, the weight was reflected and compared by employment, production, and investment sectors of the digital bio-healthcare industry. As a result of the analysis, first, the employment sector had a higher effect than the average of the entire industry, second, the production sector was low, and third, the investment sector required investment in the service sector. The conclusions drawn from the analysis showed that direct investment and continuous investment are required in the employment sector, the development of professional manpower is urgent, and direct investment and long-term investment are effective in the production sector.

• The Journal of Industrial Distribution & Business
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• v.9 no.9
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• pp.35-44
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• 2018

Purpose - In endless competition, companies pursue cost reduction and work efficiency. So, entrepreneurs try to increase job intensity, which may lead to job stress and high turnovers because of job burnout. But, Information systems are acknowledged as a work support tool that secures work convenience and the productivity of employees. In this study, we aimed to confirm the effects of information systems in reduing the work overload of employees in a human resource intensive industry. Research design, data and methodology - This is based on the job demands-resources model, conducting an empirical analysis of surveys given to hospital employees working in a human resource intensive industry. Results - The research revealed that information systems reduced the work overload of employees in a human resource intensive industry. Conclusion - This study confirmed the effects of information systems as a job resource based on JD-R theory, and presentation of empirical results indicated that information systems alleviate employee job overload and increases job satisfaction in the medical services industry. In the medical services industry, using electronic health record system decreases in work overload, which results in employees gaining time for self-development and time management, reducing job stress, and leading to job satisfaction.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.327-334
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• 2018

Objectives: The objective of this study was to investigate the relationship between the level of Electronic Medical Record (EMR) system adoption and healthcare information technology (IT) infrastructure. Methods: Both survey and various healthcare administrative datasets in Korea were used. The survey was conducted during the period from June 13 to September 25, 2017. The chief information officers of hospitals were respondents. Among them, 257 general hospitals and 273 small hospitals were analyzed. A logistic regression analysis was conducted using the SAS program. Results: The odds of having full EMR systems in general hospitals statistically significantly increased as the number of IT department staff members increased (odds ratio [OR] = 1.058, confidence interval [CI], 1.003-1.115; p = 0.038). The odds of having full EMR systems was significantly higher for small hospitals that had an IT department than those of small hospitals with no IT department (OR = 1.325; CI, 1.150-1.525; p < 0.001). Full EMR system adoption had a positive relationship with IT infrastructure in both general hospitals and small hospitals, which was statistically significant in small hospitals. The odds of having full EMR systems for small hospitals increased as IT infrastructure increased after controlling the covariates (OR = 1.527; CI, 1.317-4.135; p = 0.004). Conclusions: This study verified that full EMR adoption was closely associated with IT infrastructure, such as organizational structure, human resources, and various IT subsystems. This finding suggests that political support related to these areas is indeed necessary for the fast dispersion of EMR systems into the healthcare industry.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.91-101
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• 2010

By using the U-Healthcare environment, it is possible to receive the health care services anywhere anytime. However, since the user's personal information can be easily exposed in the U-Healthcare environment, it is necessary to strengthen the security system. This thesis proposes the technique which can be used to protect the personal medical records at hospital safely, in order to avoid the exposure of the user's personal information which can occur due to the frequent usage of the electronic chart according to the computerization process of medical records. In the proposed system, the following two strategies are used: i) In order to reduce the amount of the system load, it is necessary to apply the partial encryption process for electronic charts. ii) Regarding the user's authentication process for each patient, the authentication number for each electronic chart, which is in the encrypted form, is transmitted through the patient's mobile device by the National Health Insurance Corporation, when the patient register his or her application at hospital. Regarding the modern health care services, it is important to protect the user's personal information. The proposed technique will be an important method of protecting the user's information.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.1
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• pp.19-29
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• 2011

The u-Healthcare system, a new paradigm, provides healthcare and medical service anytime, anywhere in daily life using wired and wireless networks. It only doesn't reach u-Hospital at home, to manage efficient personal health in fitness space, it is essential to feedback process through measuring and analyzing a personal vital signs. MBAN(Medical Body Area Network) is a core of this technology. MBAN, a new paradigm of the u-Healthcare system, can provide healthcare and medical service anytime, anywhere on real time in daily life using u-sensor networks. In this paper, an ontology-based context-awareness in MBAN proposed system development methodology. Accordingly, ontology-based context awareness system on MBAN to Elderly/severe patients/aged/, with measured respiratory rate/temperature/pulse and vital signs having small variables through u-sensor network in real-time, discovered abnormal signs and emergency situations which may happen to people at sleep or activity, alarmed and connected with members of a family or medical emergency alarm(Emergency Call) and 119 system to avoid sudden accidents for early detection. Therefore, We have proposed that accuracy of biological signal sensing and the confidence of ontology should be inspected.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.7-14
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• 2021

With the increased attention about healthcare and management of heart diseases, smart healthcare services and related devices have been actively developed recently. R wave is the largest representative signal among ECG signals. R wave detection is very important because it detects QRS pattern and classifies arrhythmia. Several R wave detection algorithms have been proposed with different features, but the remaining problem is their implementation in low-cost portable platforms for real-time applications. In this paper, we propose R wave detection based on optimal threshold and arrhythmia classification through QRS pattern considering complexity in smart healthcare environments. For this purpose, we detected R wave from noise-free ECG signal through the preprocessing method. Also, we classify premature ventricular contraction arrhythmia in realtime through QRS pattern. The performance of R wave detection and premature ventricular contraction arrhythmia classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction. The achieved scores indicate the average of 98.72% in R wave detection and the rate of 94.28% in PVC classification.