• 의료법학
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• 제13권1호
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• pp.359-395
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• 2012

In a broad term, health and medical data means all patient information that has been generated or circulated in government health and medical policies, such as medical research and public health, and all sorts of health and medical fields as well as patients' personal data, referred as medical data (filled out as medical record forms) by medical institutions. The kinds of health and medical data in medical records are prescribed by Articles on required medical data and the terms of recordkeeping in the Enforcement Decree of the Medical Service Act. As EMR, OCS, LIS, telemedicine and u-health emerges, sharing and protecting digital health and medical data is at issue in these days. At medical institutions, health and medical data, such as medical records, is classified as "sensitive information" and thus is protected strictly. However, due to the circulative property of information, health and medical data can be public as well as being private. The legal grounds of health and medical data as such are based on the right to informational self-determination, which is one of the fundamental rights derived from the Constitution. In there, patients' rights to refuse the collection of information, to control recordkeeping (to demand access, correction or deletion) and to control using and sharing of information are rooted. In any processing of health and medical data, such as generating, recording, storing, using or disposing, privacy can be violated in many ways, including the leakage, forgery, falsification or abuse of information. That is why laws, such as the Medical Service Act and the Personal Data Protection Law, and the Guideline for Protection of Personal Data at Medical Institutions (by the Ministry of Health and Welfare) provide for technical, physical, administrative and legal safeguards on those who handle personal data (health and medical information-processing personnel and medical institutions). The Personal Data Protection Law provides for the collection, use and sharing of personal data, and the regulation thereon, the disposal of information, the means of receiving consent, and the regulation of processing of personal data. On the contrary, health and medical data can be inspected or delivered of the copies, based on the principle of restriction on fundamental rights prescribed by the Constitution. For instance, Article 21(Access to Record) of the Medical Service Act, and the Personal Data Protection Law prescribe self-disclosure, the release of information by family members or by laws, the exchange of medical data due to patient transfer, the secondary use of medical data, such as medical research, and the release of information and the release of information required by the Personal Data Protection Law.

• 의학교육논단
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• 제25권2호
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• pp.126-131
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• 2023

The aim of this study was to systematically collect data for evaluating short- and long-term outcomes using Kirkpatrick's four-level evaluation model, Chonnam National Medical School has established plans for developing and managing a database of student and graduate cohorts. The Education Evaluation Committee, with assistance from the Medical Education Office, manages the development and maintenance of cohort data. Data collection began in the 2022 academic year with first- through fourth-year medical students and graduates of the year 2022. The collected data include sociodemographic characteristics, admission information, psychological test results, academic performance data, extracurricular activity data, scholarship records, national medical licensing exam results, and post-graduation career paths. The Education Evaluation Committee and the Medical Education Office analyze the annually updated student and graduate cohort data and report the results to the dean and relevant committees. These results are used for admissions processes, curriculum improvement, and the development of educational programs. Applicants interested in using the student and graduate cohort data to evaluate the curriculum or conduct academic research must undergo review by the Educational Evaluation Committee before being granted access to the data. It is expected that the collected data from student and graduate cohorts will provide a sound and scientific basis for evaluating short- and long-term achievements based on student, school, and other characteristics, thereby supporting medical education policies, innovation, and implementation.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.257-264
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• 2003

The perception of the importance of statistical methods for processing medical data in Korea's medical research and the practical use of the analysis method are insufficient. From this standpoint, in order to examine the features of the data analysis method used in the medical journals of Korea and America, we have examined the research papers which has been published in the exemplary medical journals of both countries. It showed that there was a large difference in the quantity and quality between Korea and America. Especially in the medical research of Korea, we could notice that the use of statistical methods were comparatively low. Hence the researchers in the medical area are encouraged to use more statistical methods in processing medical data.

• 한국인공지능학회지
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• 제10권2호
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• pp.13-18
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• 2022

The role of artificial medical intelligence through medical big data has been focused on data-based medical device business and medical service technology development in the field of diagnostic examination of the patient's current condition, clinical decision support, and patient monitoring and management. Recently, with the 4th Industrial Revolution, the medical field changed the medical treatment paradigm from the method of treatment based on the knowledge and experience of doctors in the past to the form of receiving the help of high-precision medical intelligence based on medical data. In addition, due to the spread of non-face-to-face treatment due to the COVID-19 pandemic, it is expected that the era of telemedicine, in which patients will be treated by doctors at home rather than hospitals, will soon come. It can be said that artificial medical intelligence plays a big role at the center of this paradigm shift in prevention-centered treatment rather than treatment. Based on big data, this paper analyzes the current status of artificial intelligence technology for chronic disease patients, market trends, and domestic and foreign company trends to predict the expected effect and future development direction of artificial intelligence technology for chronic disease patients. In addition, it is intended to present the necessity of developing digital therapeutics that can provide various medical services to chronically ill patients and serve as medical support to clinicians.

• 대한의용생체공학회:의공학회지
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• 제42권6호
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• pp.259-267
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• 2021

Recently, the market for personal health care and medical devices based on Bluetooth Low Energy(BLE) has grown rapidly. BLE is being used in various medical data communication devices based on low power consumption and universal compatibility. However, since data errors occurring in the transmission of medical data can lead to medical accidents, it is necessary to analyze the causes of errors and study methods to reduce data error. In this paper, the minimum communication speed to be used in medical devices was set to at least 800 byte/sec based on the wireless electrocardiography regulations of the Ministry of Food and Drug Safety. And the data loss rate was tested when data was transmitted at a speed higher than 800 byte/sec. The factors that cause communication data error were classified, and the relationship between each factor and the data error rate was analyzed through experiments. When there were two or more activated peripherals connected to the central, data error occurred due to channel hopping and bottleneck, and the data error rate increased in proportion to the communication distance and the number of activated peripherals. Through this experiment, when the BLE is used in a medical device that intermittently transmits biosignal data, the risk of a medical accident is predicted to be low if the number of peripherals is 3 or less. But, it was determined that BLE would not be suitable for the development of a biosignal measuring device that must be continuously transmitted in real time, such as an electrocardiogram.

• Journal of Information Technology Applications and Management
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• 제12권2호
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• pp.129-143
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• 2005

In recent years, two major streams in medical information systems are：1) system integration among OCS(Order Communication System), EMR(Electronic Medical Record), PACS(Picture Archiving and Communication System), and ERP(Enterprise Resource Planning) and 2) system integration through medical collaboration between East and West medical service providers. One of the characteristics which differentiate the Korean medical industry from the western medical industry is the East-West medical collaboration. In many respects there are many differences between East and West medical treatment. Although East and West medical treatment have developed from different medical philosophies and standards, we assume that the better medical care can be provided by integrating their medical procedures effectively. The two possible approaches to the integration of East and West medical information systems are suggested in this paper：One is loosely coupled model and the other is tightly coupled model. EMR improves the quality of medical record which reflects the quality of clinical practice. It provides more efficient and convenient way of input, retrieval, storage, communication and management of medical data. We abstracted the standard medical procedures from the two medical procedures performed in Daejeon Oriental Hospital and Hehwa Clinic at Daejeon University and also abstracted database schema by analyzing the characteristics of information needed in East-West medical collaboration. Our EMR is composed of two types of data：one is structured data and the other is unstructured data, which are formalized by SOAP(Subjective, Objective, Assessment, Plan) format. Currently the integrated system is implemented and operated successfully for six months.

• 한국IT서비스학회지
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• 제23권3호
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• pp.39-54
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• 2024

This study explores the barriers to using health and medical data in research and development (R&D) within the healthcare industry and suggests ways to enhance data utilization. As artificial intelligence technology drives transformative changes across industries, there is an increased demand for robust health and medical data, highlighting its critical economic value and utility in fostering innovation. Using qualitative analysis through Grounded Theory, the study involves ten R&D professionals from healthcare industry, including both medical centers and corporations, using surveys and in-depth interviews to gather diverse experiences and perspectives on the challenges and opportunities in health and medical data use. Key findings point to legislative, regulatory, and data quality and integration issues, as well as complexities in patient data access and usage. Technological limitations and inadequate data governance frameworks also emerge as significant obstacles. Recommendations focus on improving regulatory frameworks, enhancing data standardization and quality, and fostering stronger partnerships between data custodians and users. The study concludes that overcoming these obstacles requires a comprehensive strategy involving legislative changes, improved technological infrastructure, and increased stakeholder collaboration. Implementing these recommendations could greatly enhance health and medical data utilization in R&D, significantly advancing medical science and patient care services.

• 대한의용생체공학회:의공학회지
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• 제26권6호
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• pp.399-406
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• 2005

In these days, HIS(Hospital Information System) raise the quality of medical services by effective management of medical records. As computing environment was developed, it is possible to search information quickly. But, standard medical data exchange is not completed between medical clinic and another organ so far. In case of patient transfer, past medical record was not efficiently transmitted. It be feasible treatment delay or medical accident. It is trouble that medical records is transferred by a person and communicate with each other. Extensible Markup Language (XML) is a simple, very flexible text format derived from SGML. Originally designed to meet the challenges of large-scale electronic publishing, XML is also playing an increasingly important role in the exchange of a wide variety of data on the Web and elsewhere. Form in system of company product, relative organs that handle bio-signal data is each other dissimilar and integration and to transmit to supplement bottleneck this research uses XML. In this study, it is discussed about sharing of medical data using XML web technology to standard medical record between hospital and relative organization The data structure model was designed to manage bio-signal data and patient record. We experimented about data transmission and all-in-one between different systems (one make use of MS-SQL database system and the other manage existent bio-signal data in itself form in file in this research). In order to search and refer medical record, the web-based system was implemented. The system that can be shared medical data was tested to estimate the merits of XML. Implemented XML schema confirms data transmission between different data system and integration result.

• 한국전자통신학회논문지
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• 제10권12호
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• pp.1403-1410
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• 2015

본 연구에서는 병원정보시스템에서 분야별로 발생하는 의료 빅데이터 자료를 활용하여 가치있는 의료정보를 생성하고 활용할 수 있는 방안을 마련하고자 한다. 본 연구의 결과는 첫 번째, 의료정보시스템의 진료정보와 각종 검사장비 및 의료영상장비와 연동된 PACS의 발생자료를 통합하고 의료 빅데이터를 분석하여 새로운 의료정보를 생성한다. 이렇게 생성된 의료정보는 감염병 및 질병 예방과 질병의 치료를 위한 다양한 건강정보를 생성하게 된다. 두 번째, 환자의 접수내역과 수납내역 그리고 청구내역들을 통합하여 축적해온 의료 빅데이터를 분석하여 다양한 수익통계정보를 생성한다. 이렇게 생성된 수익통계정보는 의료기관의 운영과 수익분석에 활용하기 위한 다양한 경영정보를 생성하게 된다. 이와 같이 병원정보시스템에서 발생하는 의료정보와 공공기관의 의료정보 그리고 개인건강기록의 자료들이 통합이 되면 의료자료를 활용한 가치있는 보건의료정보를 창출하게 된다.

• Asian Pacific Journal of Cancer Prevention
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• 제14권3호
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• pp.2107-2111
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• 2013

Objectives: To investigate data agreement of cancer registries and medical records as well as the quality of care and assess their relationship in a 5-year period from 2006 to 2011. Methods: The present cross-sectional, descriptive-analytical study was conducted on 443 cases summarized through census and using a checklist. Data agreement of Nemazi hospital-based cancer registry and the breast cancer prevention center was analyzed according to their corresponding medical records through adjusted and unadjusted Kappa. The process of care quality was also computed and the relationship with data agreement was investigated through chi-square test. Results: Agreement of surgery, radiotherapy, and chemotherapy data between Nemazi hospital-based cancer registry and medical records was 62.9%, 78.5%, and 81%, respectively, while the figures were 93.2%, 87.9%, and 90.8%, respectively, between breast cancer prevention center and medical records. Moreover, quality of mastectomy, lumpectomy, radiotherapy, and chemotherapy services assessed in Nemazi hospital-based cancer registry was 12.6%, 21.2%, 35.2%, and 15.1% different from the corresponding medical records. On the other hand, 7.4%, 1.4%, 22.5%, and 9.6% differences were observed between the quality of the above-mentioned services assessed in the breast cancer prevention center and the corresponding medical records. A significant relationship was found between data agreement and quality assessment. Conclusion: Although the results showed good data agreement, more agreement regarding the cancer stage data elements and the type of the received treatment is required to better assess cancer care quality. Therefore, more structured medical records and stronger cancer registry systems are recommended.