• Journal of muscle and joint health
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• v.14 no.1
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• pp.13-25
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• 2007

Purpose: The purpose of the study was to identify the effects of Tai Chi self-help program on glucose control, cardiovascular risks, and quality of life in patients with type II diabetes. Method: The study subjects were 95 adults with type II diabetes recruited from five primary health centers and one outpatient clinic. The Tai chi self-help program was provided twice a week for 6 months. Outcome measures included blood glucose(HbA1c), cardiovascular risk checklist, and quality of life(SF36). Result: At the completion of 6-month program, HbA1c for Tai Chi group dropped from 6.79 to 6.59 without significant group differences. However, cardiovascular risk scores for Tai Chi group has been significantly reduced compared to the control group. In 6 months, quality of life (SF36) was significantly better for Tai Chi group especially in the areas of physical and social functioning. Conclusion: Tai Chi self-help program applied for type 2 diabetes patients has been partially effective to control cardiovascular risk factors, and some dimensions of quality of life. Tai Chi self-help program can be safely and easily applicable to primary care centers for diabetic patients and other people with chronic disease for their symptom management, and health promotion.

• Journal of the Korean Dietetic Association
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• v.14 no.4
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• pp.351-360
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• 2008

The principal objective of this study was to determine the importance of obesity management nutrition programs for obese male workers after performing a 10-week nutrition program and to compare changes in the obesity index, health behavior, meal intake, and blood constituents. The study subjects included 44 individuals, all without chronic disease. After the program, the weight, body mass index (BMI), body fat percentage, and waist-hip ratio (WHR) of the subjects dropped. Dietary life behavior scores increased. In particular, more than 30% increases were detected in self-control of surfeit, control of eating speed, temperance, and regular exercise items. Total caloric intake and average drinking intake dropped. Though insignificant, systolic pressure, total cholesterol, LDL-cholesterol, and sGPT all dropped as compared to the levels measured prior to the program. Fasting blood sucrose, triglyceride, $\gamma$-GTP, and atherogenic index dropped significantly. HDL-cholesterol, though insignificant, increased. As the result of examining correlations between the subjects' health life behavior, caloric intake, and improvement in obesity, we noted a significant correlation between self-control of surfeit and temperance in the health life behavior item, along with significant correlations among total calorie intake, surfeit percentage, and daily average drinking intake. These results demonstrated that nutrition program for obese workers performed at the Community Health Center had the effect of reducing obesity, improving health behavior, and improving clinical levels. Thus, it is advisable that obesity management programs be achieved, linking the center of local societies' health promotion projects, community health centers, and workplaces, and various programs should be developed to maintain and continue changes in workers' behaviors, such that the positive effects of improvement in obesity could be maintained, even after the program.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.149-157
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• 2014

Diabetes is a chronic disease that requires continuous medical care and patient-self management education to prevent acute complications and reduce the risk of long-term complications. The worldwide prevalence and incidence of diabetes mellitus are reached epidemic proportions in most populations. Early detection of diabetes could help to prevent its onset by taking appropriate preventive measures and managing lifestyle. The major objective of this research is to develop an automated decision support system for detection of diabetes using mixture of experts model. The performance of the classification algorithms was compared on the Pima Indians diabetes dataset. The result of this study demonstrated that the mixture of expert model achieved diagnostic accuracies were higher than the other automated diagnostic systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1321-1322
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• 2012

With the advance of Information Technology (IT) and dynamic requirements, diverse application services have been provided for end users. With huge volume of these services and information, users are required to acquire customized services that provide personalized information and decision at particular extent of time. The case is more appealing in healthcare, where patients wish to have access to their medical record where they have control and provided with recommendation on the medical information. PHR (Personal Health Record) is most prevailing initiative that gives secure access on patient record at anytime and anywhere. PHR should also incorporate decision support to help patients in self-management of their diseases. Available PHR system incorporates basic recommendations based on patient routine data. We have proposed decision support service called "Smart CDSS" that provides recommendations on PHR data for diabetic patients. Smart CDSS follows HL7 vMR (Virtual Medical Record) to help in integration with diverse application including PHR. PHR shares patient data with Smart CDSS through standard interfaces that pass through Adaptability Engine (AE). AE transforms the PHR CCR/CCD (Continuity of Care Record/Document) into standard HL7 vMR format. Smart CDSS produces recommendation on PHR datasets based on diabetic knowledge base represented in shareable HL7 Arden Syntax format. The Smart CDSS service is deployed on public cloud over MS Azure environment and PHR is maintaining on private cloud. The system has been evaluated for recommendation for 100 diabetic patients from Saint's Mary Hospital. The recommendations were compared with physicians' guidelines which complement the self-management of the patient.

• Health Policy and Management
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• v.31 no.4
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• pp.508-517
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• 2021

Background: After the first case of coronavirus disease 2019 (COVID-19) in January 2020, Korea has experienced three waves in 2020. This study aimed to analyze changes in health care utilization according to the period of the 1st to 3rd waves of the COVID-19 pandemic. Methods: We analyzed 3,354,469,401 national health insurance claims from 59,104 medical facilities between 2017 and 2020. Observed-to-expected ratios (O:E ratio) with data from 2017 to 2019 as expected values and data from 2020 as observed values were obtained to analyze changes in medical utilization. T-test was used to test whether the difference of observed and expected values was statistically significant. Results: In 2020, the O:E ratio was 0.894, indicating a decrease in health care utilization overall during the pandemic. The O:E ratio of the 1st wave was 0.832, which was lower than those of the second (0.886) and third (0.873) waves. Health care utilization decreased relatively more among outpatient, women, children and adolescents, and health insurance patients. And health care utilization decreased more in small medical facilities and in Daegu and Gyeongbuk during the first wave. During the pandemic, the O:E ratios of respiratory diseases were 0.486-0.694, while chronic diseases and mental diseases were more than 1.0. Conclusion: Health care utilization decreased during the COVID-19 pandemic overall, and there were differences by COVID-19 waves, and by the characteristics of patients and medical facilities. It is necessary to understand the cause of changes in health care utilization in order to cope with the prolonged COVID-19 pandemic.

• Journal of The Korea Institute of Healthcare Architecture
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• v.25 no.1
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• pp.17-27
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• 2019

Purpose: Clinical laboratory in hospital has taken a great role in protection of chronic disease. as well as diagnosis and treatment, And laboratory layout has been considered by the management and laboratory section more than the function and workflow. Methods: So this study figures out the workflows of laboratory sections in the recently upgraded Laboratory Medicine, and searches the functional relationships and spatial block diagram between each disciplines as follows. Literature review and expert adviser has been conducted. Results: 1) Laboratory type of Laboratory Medicine is divided into routine and specialized laboratory according to the workflow by automated or specialized test. 2) The general workflow consists of specimen collection, specimen classification, test by discipline, test report, and specimen disposal. 3) Though the function of each laboratory section is very complicated and specific, the characteristics and the workflow can be shown in detail by each lab through [Figure 4], [Figure 5], [Figure 6], [Figure 7], and [Figure 8]. 4) Functional relationship diagram can be displayed to the adjacency and relation between each laboratory and support spaces. 5) The spatial block diagram could be presented as shown in [Figure 10], in which the emergency lab lay in front side, routine lab in the central open area, and specialized lab in the behind side. Implications: This study can be used as a useful data in planning and designing a Laboratory Medicine Department.

• Health Policy and Management
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• v.29 no.2
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• pp.160-171
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• 2019

Background: This study purposed to compare the difference on medical utilization and health expenditure of baby boomer generation by depression between gender. Methods: Korea Welfare Panel Survey 2016, provided by the Korea Institute for Health and Social Affairs, was used for the analysis. For the research, we used the two-part model, yes or no of use (part 1), and frequency of use (part 2) for medical utilization. The dependent variables are the whether or not to use of hospitalization services, outpatient services, length of stay, outpatient service visits, and health expenditure. And the independent variables are used as the predisposing (education, spouse presence), enabling (insurance type, private insurance, economic activity, income), and need (chronic disease, self-rated health, disability) factors in the Andersen behavior model. Depression was used as intervening variables. Structural equation model and multiple group analysis by gender were used. Results: There were differences in the medical care usage and cost between men and women in baby boomer. For men, mediating effects of depression were present at the hospitalization (yes/no), length of stay, and health expenditure. On the other hand, for women, the mediating effect of depression was found only at the outpatient visits. Specially, depression was working at the medical services by the different way between gender. The size of effect (multiple group analysis) was affected by significant differences between men and women. Conclusion: This study found that the mediating effect of depression is increased medical usage and health expenditure and the effect factors are different by gender. Therefore, it is necessary to establish a medical care policy considering the socio-economic characteristics of baby boomers.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.89-98
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• 2021

Community-acquired pneumonia (CAP) is a major risk factor of mortality in chronic obstructive pulmonary disease (COPD). Streptococcus pneumoniae (colloquially known as pneumococcus) is one of important pathogens of CAP in patients with COPD. Preventive interventions for pneumonia include pneumococcal and influenza vaccinations. A prospective, cohort study has been performed to investigate the protective effects of pneumococcal and influenza vaccinations on the severity of community-acquired pneumonia requring hospital admission in patients with COPD. Seven university-affiliated hospitals in Korea have participated in the study. The aim of this study was to construct an online registration system for the multi-institutional researchers that facilitates efficient collection and management of COPD patient data. This study has presented three basic strategies-accurate data input, convenient data completion, and real-time data management-to supplement the demerits of existing offline clinical study. The proposed online registration system has already been applied to a multi-institutional clinical study and was acknowledged for its high performance.

• Journal of Korean Academy of Oral Health
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• v.41 no.1
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• pp.43-49
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• 2017

Objectives: In this study, we strived to determine the possibility of socioeconomic welfare in oral healthcare by analyzing the National Health Insurance (NHI) coverage rate. To date, efforts to realize the "social economy" of healthcare are active. While oral disease is common and chronic among Koreans, the rate of NHI coverage of dental clinics is substantially lower than that of the medical clinics. Methods: We defined the NHI coverage of dental clinics as a proxy for "social skills" to improve oral health problems. The data were collected through a comparative analysis of the NHI coverage of dental clinics and that of non-dental clinics, in health welfare social cooperatives. Results: The NHI coverage rate of the dental clinics in health welfare social cooperatives ranged from 0.97 to 2.62 times that of the non-dental clinics in health welfare social cooperatives. Conclusions: In conclusion, responsible management is recommended for making health welfare social cooperatives meaningful as a social economy.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.491-498
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• 2022

In our daily life, quality of sleeping is closely related to happiness index. Whether or not people perceive sleep disturbance as a chronic disease, people complain of many difficulties, and in their daily life, they often experience difficulty breathing during sleep. It is very important to automatically recognize breathing-related disorders during a sleep, but it is very difficult in reality. To solve this problem, this paper proposes a mobile-based non-contact sleeping monitoring for health management at home. Respiratory signals during the sleep are collected by using the sound sensor of the smartphone, the characteristics of the signals are extracted, and the frequency, amplitude, respiration rate, and pattern of respiration are analyzed. Although mobile health does not solve all problems, it aims at early detection and continuous management of individual health conditions, and shows the possibility of monitoring physiological data such as respiration during the sleep without additional sensors with a smartphone in the bedroom of an ordinary home.