• The Journal of Internal Korean Medicine
• /
• v.42 no.4
• /
• pp.563-571
• /
• 2021

Objectives: This pilot study aimed to confirm the possibility of applying our design to the main study, a retrospective medical record analysis of the diseases which have most frequently been treated with collaborations of Korean and Western medicine, and to identify what corrections and statistical models are needed to conduct the main study. Methods: Data were collected from a case report form developed for patients who received treatment in the medical institutions. Appropriate statistical techniques, like Propensity Score (PS) and Generalized Estimation Equation (GEE) models, were used to compare the indicators of collaboration and non-collaboration groups for patients in comparable diseases. Results: Using PS matching for each M and S disease group, the indicators were compared by balancing the collaboration and non-collaboration group, and the GEE models compared indicators between groups in each disease over follow-up. Through this process we identified two limitations, insufficient samples and a large deviation of the follow-up period. Conclusion: This pilot study confirmed that the study design and case report form are applicable. The main study will be conducted by collecting sufficient samples and reflecting deviation of follow-up period.

• Korea Journal of Hospital Management
• /
• v.17 no.1
• /
• pp.79-112
• /
• 2012

The purpose of this study is to examine the differences of profitability based on the analysis of business and medical service performances of four hospitals in Incheon area with similar size. and to compare hospitals with the best and the worst performances and analyze the factors behind the differences. The differences could be caused by differences in medical service statistics, number of staff, and financial results, etc. The data was acquired through the homepage of the National Tax Service(financial statements for the fiscal year 2009) and the Medical Record Association of Incheon(medical service statistics for the years 2008 and 2009) along with questionnaire survey to the hospitals(personnel data for the year 2009). The results of the study are as follows. Medical profits to medical revenues ratio for the hospitals(referred as Hospital A, B, C, and D) shows, in order, C(8.2%), A(8.0%), B(7.8%), and D(7.4%). However, net income to medical revenues ratio shows otherwise: C(8.5%), D(5.8%), A(3.0%), and B(0.6%). Hospital B shows a high medical profit to revenue ratio but the lowest net income to revenue ratio due to large interest expenses. The leverage ratio of Hospital B is the highest (419.6%), resulting in a very low interest coverage ratio(1.1). On the other hand, Hospital C shows favorable results in both profit ratios, with 8.2% and 8.5% each. Hospital C has the lowest leverage ratio(53.0%) and the highest interest coverage ratio(34.9). Therefore, the results show Hospital C has the best performance while Hospital B the worst. The two hospitals(B and C) show similar results in certain areas and big differences in other areas. The area that has the biggest influence on financial results turns out leverage ratio. Hospital B shows 'very good' to 'good' results in terms of medical service statistics in general. However, the leverage ratio is too high and the liquidity ratio too low, resulting in a very low profit ratio. The results of this study have some limitations in terms of generalization as only four hospitals in Incheon area were selected for the study, resulting in a deficiency in the representativeness of the sample. Further studies with bigger sample size and deeper analysis are expected in this area.

• Journal of the Institute of Convergence Signal Processing
• /
• v.25 no.2
• /
• pp.100-112
• /
• 2024

This study investigates the ethical and legal implications of utilizing artificial intelligence (AI) in human resource management, with a particular focus on AI interviews in the recruitment process. AI, defined as the capability of computer programs to perform tasks associated with human intelligence such as reasoning, learning, and adapting, is increasingly being integrated into HR practices. The deployment of AI in recruitment, specifically through AI-driven interviews, promises efficiency and objectivity but also raises significant ethical and legal concerns. These concerns include potential biases in AI algorithms, transparency in AI decision-making processes, data privacy issues, and compliance with existing labor laws and regulations. By analyzing case studies and reviewing relevant literature, this paper aims to provide a comprehensive understanding of these challenges and propose recommendations for ensuring ethical and legal compliance in AI-based HR practices. The findings suggest that while AI can enhance recruitment efficiency, it is imperative to establish robust ethical guidelines and legal frameworks to mitigate risks and ensure fair and transparent hiring practices.

• Korean Journal of Artificial Intelligence
• /
• v.7 no.2
• /
• pp.19-24
• /
• 2019

Lung cancer is a chronic disease which ranks fourth in cancer incidence with 11 percent of the total cancer incidence in Korea. To deal with such issues, there is an active study on the usefulness and utilization of the Clinical Decision Support System (CDSS) which utilizes machine learning. Thus, this study reviews existing studies on artificial intelligence technology that can be used in determining the lung cancer, and conducted a study on the applicability of machine learning in determination of the lung cancer by comparison and analysis using Azure ML provided by Microsoft. The results of this study show different predictions yielded by three algorithms: Support Vector Machine (SVM), Two-Class Support Decision Jungle and Multiclass Decision Jungle. This study has its limitations in the size of the Big data used in Machine Learning. Although the data provided by Kaggle is the most suitable one for this study, it is assumed that there is a limit in learning the data fully due to the lack of absolute figures. Therefore, it is claimed that if the agency's cooperation in the subsequent research is used to compare and analyze various kinds of algorithms other than those used in this study, a more accurate screening machine for lung cancer could be created.

• Journal of Internet Computing and Services
• /
• v.19 no.2
• /
• pp.1-7
• /
• 2018

Due to advances in DNA sequencing technologies, its medical value continues to grow. However, once genome data leaked, it cannot be revoked, and disclosure of personal genome information impacts a large group of individuals. Therefore, secure techniques for managing genomic big data should be developed. We first propose a privacy-preserving inner product protocol for large data sets using the homomorphic encryption of Gentry et al., and then we introduce an efficient privacy-preserving DNA matching protocol based on the proposed protocol. Our efficient protocol satisfies the requirements of correctness, confidentiality, and privacy.

• The Korean Journal of Health Service Management
• /
• v.14 no.1
• /
• pp.93-102
• /
• 2020

Objectives: This study analyzed the prescription characteristics of medication for acute respiratory diseases before and after pay-for-performance to provide basic data on effective medical quality management policies. Methods: The research data were collected from the 2013-2014 sample cohort of the National Health Insurance Corporation, from Internal Medicine, Pediatrics, Otorhinolaryngology, Family Medicine and General practitioner clinics (classification of disease codes: J00-J06, J20-J22, J40 outpatients). Results: The antibiotics prescription rates decreased from 43.9% in 2013 to 43.5% in 2014 when the major diagnosis was for upper respiratory infections and increased from 62.0% in 2013 to 62.5% in 2014 when the major diagnosis was for lower respiratory infections. Conclusions: There is a need to identify the correct antibiotic prescription method by expanding the current assessment standards. Such standards must include acute lower respiratory infections and minor diagnoses as the current evaluation techniques focus only on the major diagnosis of acute upper respiratory infections.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.282-285
• /
• 2018

The purpose of this study is to investigate the effect of personal factors and community factors on the quality of life based on the presence of chronic diseases based on the Big Data Platform. The research methodology was the matching of the 2017 Community Health Survey data and the National Statistical Office data to the health center units. In the study, The higher the age, the higher the education level, the higher the monthly household income, the economic activity, the spouse, the higher the quality of life. In the case of community factors, the lower the population density, the lower the elderly population ratio, the more doctors engaged in medical institutions, the higher the financial independence, the higher the quality of life.

• Journal of Korean society of Dental Hygiene
• /
• v.21 no.2
• /
• pp.119-128
• /
• 2021

Objectives: The aim of this study was to investigate the effect of breastfeeding on the occurrence of early childhood caries in Korean infants and toddlers. Methods: Data on oral examinations of infants and toddlers of the National Health Insurance Service were analyzed. The study subjects were children who participated in both the first, second, and third oral examinations and the first general health examination in 2008-2017 (n=142,185). Based on the responses to the questionnaire, the subjects were classified into breastfeeding, formula feeding, and mixed feeding groups. The participants were monitored for the development of early childhood caries in three sequential oral examinations. Results: Based on the oral examination results conducted at 54-65 months old, the decayed-filled teeth index of the breastfeeding group was the highest (2.03±3.08), followed by the mixed (1.96±3.03) and the formula feeding groups (1.82±2.91). The Cox proportional hazard regression model including all the variables showed that the risk of developing dental caries was significantly lower in the formula (hazard ratio [HR], 0.85) and mixed feeding groups (HR, 0.91) than in the breastfeeding group. Conclusions: Breastfeeding children have a higher risk of early childhood caries; therefore, oral hygiene education and regular dental check-ups are necessary.

• The Journal of the Korea Contents Association
• /
• v.13 no.11
• /
• pp.807-814
• /
• 2013

Because there are growing demands for new information service of Korean medicine (KM) accommodated changes in the paradigm of health communication, we aimed to apply health 2.0 - which shares health information to improve individuals' health - extensively in KM. First we studied about the concepts and characteristics of health 2.0 and analyzed the pros and cons of KM information services. Finally we drew the KM health 2.0 framework from the analyzed results. KM health 2.0 framework is designed to raise the value of KM information through circulation of certified medical information to prevent medical accident. And it is also designed to integrate information through big data analysis technology from the information of individual services to recreate KM contents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.560-563
• /
• 2016

The changes in the medical and healthcare are started from the digital technology. The new field of digital healthcare has started fused with existing healthcare, medical technology, and digital technology. It can increase the service effect and reduce healthcare costs by applying ICT skills such as ICBM(Internet of Things, Cloud, Big data and Mobile), artificial intelligence, robotics, virtual, augmented reality, and wearable devices to healthcare services including healthcare, disease management. Recently there has been grafted an artificial intelligence technologies such as AlphaGo of Google and Watson of IBM onto the healthcare area. In this study, we analyze the main technology, ecosystem, platforms for digital healthcare, and lastly future changes in health care services and issues of digital healthcare.