Journal of the Korea Institute of Information and Communication Engineering
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v.23
no.11
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pp.1351-1356
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2019
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 patients based on the Big Data Platform. As a method of study, second data of 2017 community health survey and Statistics Korea by City·Gun·Gu public office were used and a multi-level analysis was conducted after separating EQ-5D index, individual factor and community factor. As a result, men, age, education level, monthly household income, having economic activity, the number of sports infrastructure were positively associated with the quality of life, and subjective health not good, extremely perceived stress were negatively associated with the quality of life. Research will continue to provide a platform independent of hardware that can utilize the cloud and open source for medical big data analysis in the future.
Soo Hyun Lee;Hakyung Kim;In-bo Han;Seung Hun Sheen;Je Beom Hong;Seil Sohn
Journal of Cerebrovascular and Endovascular Neurosurgery
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v.25
no.2
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pp.143-149
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2023
Objective: The purpose of this nationwide age- and sex- matched longitudinal study was to determine the pyogenic spondylitis (PS) increases the incidence of ischemic stroke (IS) in Korea. Methods: From the National Health Insurance Service (NHIS), we collected the patient data for the period from January 1, 2004 to December 31, 2015. PS was classified according to the International Classification of Disease codes M46.2-M46.8, M49.2, and M49.3. By using a 1:5 age- and sex- stratified matching, a total of 628 patients and 3140 control subjects were included in the study. The IS incidence rates in PS and control group was calculated by using the Kaplan-Meier method. The outcome of hazard ratio of IS was estimated by Cox proportional hazards regression analyses. This study did not exclude PS as a result of postoperative complications. Results: According to the study, 51 patients (8.12%) in the PS group and 201 patients (6.4%) in the control group experienced IS. The adjusted hazard ratio of IS in the PS group was 3.419 (95% CI: 2.473-4.729) after adjusting individual medical condition and demographics. Following the results of subgroup analysis, the risk ratio of IS was greater in most of the subgroup categories (male, female, age <65, age >65, non-diabetic, hypertensive, non-hypertensive, dyslipidemic and non-dyslipidemic subgroup). However, the risk of IS did not differ significantly in diabetic subgroup (95% CI: 0.953-4.360). Conclusions: The risk rate of IS increased in patient with pyogenic spondylitis.
This study examines the statistical relationship between medical specialists and managerial performance, using regression analysis with the number of medical specialists per 100 beds as the independent variable and the managerial performance index as the dependent variable. Managerial performance index incorporated the number of out-patients per specialist, the number of in-patients per specialist, the volume of revenue per specialist, the number of beds per specialist, and the average length of stay. To compare different groups of hospitals, dummy variable was applied to five groups of hospitals according to size: 100-299 beds, 300-599 beds, 600-899 beds, 900-1199 beds, and more than 1200 beds. The data consisted of 181 general hospitals with more than 100 beds, which included 28 public hospitals, 73 corporate hospitals, 64 university hospitals and 16 private hospitals. Of those, 87 hospitals were located in big cities and 94 hospitals in medium to small cities. This study used hospitals from the Korean Hospital Association, and data published in 2004. The collected data sample was analyzed using the SPSSWIN 12.0 version, and the study hypothesis was tested using regression analysis. The findings of this study are summarized as follows: Hypothesis 1 predicting a negative effect of the number of medical specialists on the number of out-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in all the hospital groups larger than the group of 100-299 beds. Hypothesis 2 predicting a negative effect of the number of medical specialists on the number of in-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds when compared to the group of 100-299 beds. Hypothesis 3 predicting a negative effect of the number of medical specialists on the volume of revenue per specialist was not supported. However, the analysis of dummy variable showed that the volume of revenue per specialist increased in the hospital groups of 600-899 beds, 900-1199 beds, and over 1200 beds, when compared to the group of 100-299 beds. Hypothesis 4 predicting a negative effect of the number of medical specialists on the average length of stay was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds, when compared to the group of 100-299 beds. Results of this study show that the number of the medical specialists per 100 beds is an important factor in hospital managerial performance. Most hospitals have tried to retain as many medical specialists as possible to keep the number of patients stable, to ensure adequate revenue, and to maintain efficient managerial performance. Especially, the big hospitals with greater number of beds and medical specialists have shown greater revenue per medical specialist despite the smaller number of patients per medical specialist. Findings of this study explains why hospitals in Korea are getting bigger.
Park, Dae Woong;Jeong, Hyun Hak;Jeong, Myung Jin;Ryoo, Hwa Shin
The Korean Society of Law and Medicine
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v.17
no.2
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pp.315-346
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2016
With the development of big data processing technology, the potential value of healthcare big data has attracted much attention. In order to realize these potential values, various research using the healthcare big data are essential. However, the big data regulatory system centered on the Personal Information Protection Act does not take into account the aspect of big data as an economic material and causes many obstacles to utilize it as a research purpose. The regulatory system of healthcare information, centered on the primary purpose of patient treatment, should be improved in a way that is compatible with the development of technology and easy to use for public interest. To this end, it is necessary to examine the trends of overseas legal system reflecting the concerns about the balance of protection and utilization of personal information. Based on the implications of the overseas legal system, we can derive improvement points in the following directions from our legal system. First, a legal system that specializes in healthcare information and encompasses protection and utilization is needed. De-identification, which is an exception to the Privacy Act, should also clearly define its level. It is necessary to establish a legal basis for linking healthcare big data to create synergy effects in research. It is also necessary to examine the introduction of the opt-out system on the basis of the discussion on the foreign debate and social consensus. But most importantly, it is the people's trust in these systems.
This paper presents a machine learning model that predicts stroke risks in atrial fibrillation patients using public big data. As the training data, 68 independent variables including demographic, medical history, health examination were collected from the Korean National Health Insurance Service. To predict stroke incidence in patients with atrial fibrillation, we applied deep neural network. We firstly verify the performance of conventional statistical models (CHADS2, CHA2DS2-VASc). Then we compared proposed model with the statistical models for various hyperparameters. Accuracy and area under the receiver operating characteristic (AUROC) were mainly used as indicators for performance evaluation. As a result, the model using batch normalization showed the highest performance, which recorded better performance than the statistical model.
Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence. Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service-National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models. Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell's C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.
Sheen, Seung Hun;Hong, Je Beom;Kim, Hakyung;Kim, Jimin;Han, In-bo;Sohn, Seil
Journal of Korean Neurosurgical Society
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v.65
no.4
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pp.507-513
/
2022
Objective : The goal of the following statewide age and gender-coordinated cohort study in Korea is to find out if there is a link between acute myocardial infarction (AMI) and Parkinson's disease (PD). Methods : Utilizing the National Health Insurance Sharing Service cohort, patient data were collected. Six thousand four hundred seventy-five individuals with PD were distinguished by utilizing the International Classification of Diseases 10 code G20 and have enrolled in the PD group. The number of participants decreased to 5259 after excluding 1039 patients who were hospitalized less than one time or who visited an outpatient clinic less than twice. Then, 26295 individuals were selected as part of the control group after case control matching was conducted through 1 : 5 age- and gender-coordinated matching. The Cox proportional hazard regression analysis and Kaplan-Meier method were utilized to analyze the likelihood of AMI in PD. Results : After controlling for age and gender, the hazard ratio of AMI in the PD group was 3.603 (95% confidence interval [CI], 2.837-4.577). After that, the following hazard ratio of AMI in the PD group was modified against for co-morbid medical disorders, resulting in 3.551 (95% CI, 2.795-4.511). According to a subgroup analysis, in males and females aged <65 and aged ≥65 and in the non-diabetes and diabetes, hypertension and non-hypertension, dyslipidemia and non-dyslipidemia subgroups, the AMI incidence rates were dramatically higher in the PD group compared to that of the control. Conclusion : Individuals with PD have a greater chance of AMI, according to this cross-national study.
This study is conducted to investigate the current status on the utilization of health care and plan for solving this problem. The claims data of the fiscal tear 1995 obtained from the regional health insurance society are used for the study. The main findings of the study are summarized as follows. Indexes(The Extremal Quotient(EQ), coefficients of variance(CV's))which represent the regional difference in the admission rate of the tertiary medical diagnosis group report that there is difference in quantity and quality of utilization of health care. The admission rate is lower in the big city areas, Kyoungkido, Kangwondo and Chunlapukdo. Even after age-sex adjustment, the admission rate is still low in Kangwondo, Chunlapukdo and Kyoungsangpukdo. The big city areas tend to have higher rates in the expenses per claim, hospital days per claim, and daily expenses but the rates are still low in some area in Kangwondo, Chunlanamdo and Kyoungsangpukdo. This result remains as same after age-sex adjustment. There is a large regional difference in average utilization rate for the tertiary hospital of the tertiary medical diagnosis group: 57.2%(SD 11.53). The utilization rates for the tertiary hospital in their large catchment area are 96.34%, 83.19% and 73.22% in each Kyoungin, Kyoungnam and Kyoungpuk areas whereas it is lower in a Chungpuk and Chungnam areas. The regional differences of health care utilization of the tertiary medical diagnosis group gave some relationships with their geographical characteristics such as socio-economic characteristics and supply factors of medical services. It is important that many medical policies should be developed in order to minimize and balance out the regional differences of health care utilization. The service allocation policy should include the reconstruction of manpower policy, developing the resource allocating formula, finding the self-sufficient catchment area and reforcing of public health services. Moreover, in order to achieve the balanced development by region, they should investigate and consider each county's microscopic properties under the consistent macrocopic policy. The further studies to find causes of regional difference are needed.
Images of medical treatment on PACS environment are digitized and they make saving and transmission of patient's information easy with CD format causing increase of patients transfer rate between hospital and data transmission as well. Figuring out the configuration of confining status of copied images of medical treatment with CD format and present the appropriate way of identification for personal information. 20 general hospital over 500 beds which are utilizing PACS currently. Questionnaire investigation focusing on PACS operation center and it's management people. In accordance with the law of securing personal information of public organizations, it says "Anyone who wants to see his or her information via representative he or she needs to make a letter of attorney and turn in this to the president of it's possessing facility" in the article 16. Based on the investigation of general hospital for CD copy issue status near metropolitan area, 8 out of 20, were issuing CD copy through personal identification process(the person oneself and representative) and 10 general hospital were doing by getting signature of receiptor only without identification of the person oneself and 2 general hospital confirmation process is not at all. By the law of securing personal information of public organization, article 16, confirmation process is supposed to mandate lawfully with a letter of attorney when there is any request of reading and/or copies of one's information. But in reality, there were no consistent rules on reading, the process and coverage of copy issue, rejection coverage of copy issue of CD copy in each general hospital PACS operation center. Therefore there is a big need for consolidated format which is applicable by law when the representative requests to issue of CD copy that is storing medical treatment images. By issue through this consolidated format, securing medical information of individual and systemic operation and management will be valid and effective.
Linked Open Data (LOD) is rated as the best of any kind of data disclosure, and allows you to search related data by linking them in a standard format across the Internet. There is an increasing number of cases in which relevant data are constructed in the LOD form in the global environment, but in the domestic healthcare sector, the disclosure of data in the form of LOD is still at the beginning stage. In this paper, we introduce a case of LOD platform construction that provides services by linking domestic and international related data by LOD method, based on the data of Korean medical research paper data and health care big data linkage platform. Linking all data from each DB into an LOD requires a lot of time and effort, and is basically an infrastructure task that government or public institutions should be in charge of rather than the private sector. In this study, ten domestic and foreign LOD sites were linked with only a portion of each DB, enabling users to link data from various domestic and foreign organizations in a convenient manner.
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