• The Korean Society of Law and Medicine
• /
• v.13 no.1
• /
• pp.359-395
• /
• 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.

• Korean Medical Education Review
• /
• v.25 no.2
• /
• pp.126-131
• /
• 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
• /
• v.14 no.2
• /
• pp.257-264
• /
• 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.

• Korean Journal of Artificial Intelligence
• /
• v.10 no.2
• /
• pp.13-18
• /
• 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.

• Journal of Biomedical Engineering Research
• /
• v.42 no.6
• /
• pp.259-267
• /
• 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
• /
• v.12 no.2
• /
• pp.129-143
• /
• 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.

• Journal of Biomedical Engineering Research
• /
• v.26 no.6
• /
• pp.399-406
• /
• 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.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.12
• /
• pp.1403-1410
• /
• 2015

The purpose of this study is to provide ways to utilize and create valuable medical information utilizing Medical Big Data created by field in hospital information system. The results of this study first creates new medical information of Medical Information system through medical big data analysis and integration of created data of PACS linked with many kinds of testing equipment and medical image equipment along with medical treatment information. Medical information created in this way produces various health information for treatment and prevention of disease and infectious disease. Second, it creates profit statistics information in various ways by analyzing medical big data accumulated through integration of billings and receipt, admission breakdown of patients. Profit statistics information created in this way produces various administration information to be utilized in profit anaysis and operation of medical institution. Likewise, data integration of personal health history, medical information of public institutions, medical information created in hospital information system produces valuable medical health information utilizing medical data.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.3
• /
• pp.2107-2111
• /
• 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.

• Korean Medical Education Review
• /
• v.24 no.2
• /
• pp.156-171
• /
• 2022

The purpose of this study was to establish a model for constructing longitudinal data for medical school, and to structure cohort and longitudinal data using data from Yonsei University College of Medicine (YUCM) according to the established input-environment-output (I-E-O) model. The study was conducted according to the following procedure. First, the data that YUCM has collected was reviewed through data analysis and interviews with the person in charge of each questionnaire. Second, the opinions of experts on the validity of the I-E-O model were collected through the first expert consultation, and as a result, a model was established for each stage of medical education based on the I-E-O model. Finally, in order to further materialize and refine the previously established model for each stage of medical education, secondary expert consultation was conducted. As a result, the survey areas and time period for collecting longitudinal data were organized according to the model for each stage of medical education, and an example of the YUCM cohort constructed according to the established model for each stage of medical education was presented. The results derived from this study constitute a basic step toward building data from universities in longitudinal form, and if longitudinal data are actually constructed through this method, they could be used as an important basis for determining major policies or reorganizing the curricula of universities. These research results have implications in terms of the management and utilization of existing survey data, the composition of cohorts, and longitudinal studies for many medical schools that are conducting surveys in various areas targeting students, such as lecture evaluation and satisfaction surveys.