• Korean Journal of Artificial Intelligence
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• v.10 no.2
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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.

• Health Policy and Management
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• v.32 no.2
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• pp.154-163
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• 2022

Background: The costliness index (CI) is an index that is used in various ways to improve the quality of medical care and the management of appropriate treatment in medical institutions. However, the current calculation method for CI has a limitation in reflecting the actual medical cost of the patient unit because the outpatient and inpatient costs are evaluated separately. It is desirable to calculate the CI by integrating the medical cost into the episode unit. Methods: We developed an episode-based CI method using the episode classification system of the Centers for Medicare and Medicaid Services to the National Inpatient Sample data in Korea, which can integrate the admission and ambulatory care cost to episode unit. Additionally, we compared our new method with the previous method. Results: In some episodes, the correlation between previous and episode-based CI was low, and the proportion of outpatient treatment costs in total cost and readmission rates are high. As a result of regression analysis, it is possible that the level of total medical costs of the patient unit in low volume medical institute and rural area has been underestimated. Conclusion: High proportion of outpatient treatment cost in total medical cost means that some medical institutions may have provided medical services in the ambulatory care that are ancillary to inpatient treatment. In addition, a high readmission rate indicates insufficient treatment service for inpatients, which means that previous CI may not accurately reflect actual patient-based treatment costs. Therefore, an integrated patient-unit classification system which can be used as a more effective CI indicator is needed.

• Journal of Korean Medicine for Obesity Research
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• v.17 no.1
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• pp.46-53
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• 2017

Health care big data is thought to be a promising field of interest for disease prediction, providing the basis of medical treatment and comparing effectiveness of different treatments. Korean government has begun an effort on releasing public health big data to improve the quality and safety of medical care and to provide information to health care professionals. By studying population based big data, interesting outcomes are expected in many aspects. To initiate research using health care big data, it is crucial to understand the characteristics of the data. In this review, we analyzed cases from inside and outside the country using clinical data registry. Based on successful cases, we suggest research method for evidence-based Korean medicine. This will provide better understanding about health care big data and necessity of Korean medicine data registry network.

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

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.345-352
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• 2022

Conducting AI-based fusion business due to the increment of ICT fusion medical device has been expanded. In addition, AI-based medical devices help change existing medical system on treatment into the paradigm of customized treatment such as preliminary diagnosis and prevention. It will be generally promoted to the change of medical device industry. Although the current demand forecasting of medical biotechnology commercialization is based on the method of Delphi and AHP, there is a problem that it is difficult to have a generalization due to fluctuation results according to a pool of participants. Therefore, the purpose of the paper is to predict demand forecasting for identifying promising technology based on building up big data in medical biotechnology. The development method is to employ candidate technologies of keywords extracted from SCOPUS and to use word2vec for drawing analysis indicator, technological distance similarity, and recommended technological similarity of top-level items in order to achieve a reasonable result. In addition, the method builds up academic big data for 5 years (2016-2020) in order to commercialize technology excavation on demand perspective. Lastly, the paper employs global data studies in order to develop domestic and international demand for technology excavation in the medical biotechnology field.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.101-109
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• 2014

Medical technology development and increase the income level of a "Long and healthy Life=Wellness," with the growing interest in actively promoting and maintaining health and wellness has become enlarged. In addition, the demand for personalized health care services is growing and extensive medical moves of big data, disease prevention, too. In this paper, the main interest in the market, highlighting wellness in order to support big data-driven healthcare quality through patient-centered medical services purposes. Patients with drug dependence treatment is not to diet but to improve disease prevention and treatment based on analysis of big data. Analysing your Tweets-daily information and wellness disease prevention and treatment, based on the purpose of the dictionary. Efficient big data analysis for node while increasing processing time experiment. Test result case of total access time efficient 26% of one node to three nodes and case of data storage is 63%, case of data aggregate is 18% efficient of one node to three nodes.

• The Journal of Pediatrics of Korean Medicine
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• v.36 no.2
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• pp.1-12
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• 2022

Objectives We analyzed visiting patterns to medical institutions and cost per visit according to the common cold patients aged 0-19 years. We analyzed Korean medical treatment for common cold. Methods Using the Pediatric Patient Sample data of the Health Insurance Review and Assessment Service (HIRA-PPS), we analyzed the data on health insurance claims of approximately 1 million people from 2017 to 2019. The data included the number of patients who visited the hospital due to common cold for the first and second time, the ratio of second visits by type of medical institution, and the status of prescriptions in Korean medical institutions. Results The number of patients visiting healthcare providers for common cold was higher in Western medical institutions than in Korean medical institutions. However, the number of second visits was higher in Korean medical institutions. Acupuncture is the most commonly used medical treatment in Korean medical institutions for common cold. Herbal medicine for common cold was usually prescribed for 2-3 days for children and adolescents. Conclusions Although the average medical cost of Korean medical institutions was higher than that of Western medical institutions, the rate of second visits to Korean medical institutions was higher because of the demand for Korean medical treatment

• The Journal of Korean Medicine
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• v.36 no.3
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• pp.98-110
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• 2015

Objectives: The purpose of this study was to analyze the medical cost of facial paralysis in payer perspective and to estimate the practice pattern of patient using 2011 Health Insurance Review & Assessment Service-National Patients Sample(HIRA-NPS). Methods: Basic statistical system was used for descriptive analysis of NPS dataset. A table for general information (table20) was extracted by disease code, and social demographic characteristics, distribution of the use among inpatients and outpatients, utilization of each kind of medical care institutions, medical cost were analyzed. Subgroup analysis was conducted for assuming the practice pattern of korean medicine and western medicine. Results: A total of 8,219 people and 64,345 claims data were identified as having facial paralysis. Proportion of outpatient was 95.23%, inpatient 0.84% and patient using both services 3.93%. Mean patient charges was 44,229 won per outpatient, 178,886 won per inpatient and 523,542 won per patient using both services. Utilization of korean medical care institutions was 68.81%(claims), 40.46%(patients), utilization of western medical care institutions was 31.19%(claims), 59.54%(patients). The amount charged by korean medical care institutions was 52.61% and western medical care institutions was 47.39%. Cost per claim was higher than those of the korean treatment and cost per patient of western treatment was lower than those of the korean treatment. Conclusions: The research assessed the medical cost and practice pattern associated with facial paralysis. These findings could be used in health care policy and subsequent studies.

• Health Policy and Management
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• v.28 no.3
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• pp.263-271
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• 2018

Health technology assessment (HTA) is defined as multidisciplinary policy analysis to look into the medical, economic, social, and ethical implications of the development, distribution, and use of health technology. Following the recent changes in the social environment, there are increasing needs to improve Korea's healthcare environment by, inter alia, assessing health technologies in an organized, timely manner in accordance with the government's strategies to ensure that citizens' medical expenses are kept at a stable level. Dedicated to HTA and research, the National Evidence-based Healthcare Collaborating Agency (NECA) analyzes and provides grounds on the clinical safety, efficacy, and economic feasibility of health technologies. HTA offers the most suitable grounds for decision making not only by healthcare professionals but also by policy makers and citizens as seen in a case in 2009 where research revealed that glucosamine lacked preventive and treatment effects for osteoarthritis and glucosamine was subsequently excluded from the National Health Insurance's benefit list to stop the insurance scheme from suffering financial losses and citizens from paying unnecessary medical expenses. For the development of HTA in Korea, the NECA will continue exerting itself to accomplish its mission of providing policy support by health technology reassessment, promoting the establishment and use of big data and HTA platforms for public interest, and developing a new value-based HTA system.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.21-30
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• 2021

With the rapid development of artificial intelligence and big data, a lot of medical data is effectively used, and the diagnosis and analysis of diseases has entered the era of intelligence. With the increasing public health awareness, ordinary citizens have also put forward new demands for panic disorder health services. Specifically, people hope to predict the risk of panic disorder as soon as possible and grasp their own condition without leaving home. Against this backdrop, the smart health industry comes into being. In the Internet age, a lot of panic disorder health data has been accumulated, such as diagnostic records, medical record information and electronic files. At the same time, various health monitoring devices emerge one after another, enabling the collection and storage of personal daily health information at any time. How to use the above data to provide people with convenient panic disorder self-assessment services and reduce the incidence of panic disorder in China has become an urgent problem to be solved. In order to solve this problem, this research applies the context awareness to the automatic diagnosis of human diseases. While helping patients find diseases early and get treatment timely, it can effectively assist doctors in making correct diagnosis of diseases and reduce the probability of misdiagnosis and missed diagnosis.