Sung-Hong Kang

Human amniotic fluid-derived stem cells have characteristics of multipotent stem cells

Abstract.  Objectives: To characterize mesenchymal stem cell‐like cells isolated from human amniotic fluid for a new source of therapeutic cells. Materials: Fibroblastoid‐type cells obtained from amniotic fluid at the time of birth. Methods: The ability of ex vivo expansion was investigated until senescence, and stem cell‐like characteristics were analyzed by examining differentiation potential, messenger RNA expression and immunophenotypes. Results and Conclusions: A morphologically homogenous population of fibroblastoid‐type (HAFFTs) cells, similar to mesenchymal stem cells from bone marrow (BM‐MSCs), was obtained at the third passage. The cells became senescent after 27 passages over a period of 8 months while undergoing 66 population doublings. Under appropriate culture conditions, by the 8th passage they differentiated into adipocytes, osteocytes, chondrocytes and neuronal cells, as revealed by oil red O, von Kossa, Alcian blue and anti‐NeuN antibody staining, respectively. Immunophenotype analyses at the 17th passage demonstrated the presence of TRA‐1–60; SSEA‐3 and‐4; collagen types I, II, III, IV and XII; fibronectin; α‐SMA; vimentin; desmin; CK18; CD44; CD54; CD106; FSP; vWF; CD31; and HLA ABC. Reverse transcriptase–polymerase chain reaction analysis of the HAFFTs from passages 6–20 showed consistent expression of Rex‐1, SCF, GATA‐4, vimentin, CK18, FGF‐5 and HLA ABC genes. Oct‐4 gene expression was observed up to the 19th passage but not at the 20th passage. HAFFTs showed telomerase activity at the 5th passage with a decreased level by the 21st passage. Interestingly, BMP‐4, AFP, nestin and HNF‐4α genes showed differential gene expression during ex vivo expansion. Taken together, these observations suggest that HAFFTs are pluripotent stem cells that are less differentiated than BM‐MSCs, and that their gene expression profiles vary with passage number during ex vivo expansion.

A Study on Utilization of non-residential areal in Operation patient

This study conducted a chi-square test and a logistic regression analysis by not only using a investigation data of discharged patients with damages from 2004 to 2006, but also using a census and a research data on the actual condition from health care system. The result follows; First, the centralization of medical utilization of operation patients is becoming apparent, centrally the capital area. To improve this, a policy that can not only provide medical centers and sickbed, but also improve the quality of local medical treatments for the localization of medical treatments. Second, propelling localization policy of certain diseases for the localization of medical utilization is needed as the rate of non-residential of operation patients that have diseases of the eye and adnexa, or cancers is high. Third, a localization policy for patients with damages is needed as the rate of treatments in other regions of operation patients with industrial accidents is increasing day by day.

A Study on analysis of severity-adjustment length of stay in hospital for community-acquired pneumonia

Abstract Our study was carried out to develop the severity-adjustment model for length of stay in hospital for community-acquired pneumonia so that we analysed the factors on the variation in length of stay(LOS). The subjects were 5,353 community-acquired pneumonia inpatients of the Korean National Hospital Discharge In-depth Injury Survey data from 2004 through 2006. The data were analyzed using t-test and ANOVA and the severity-adjustment model was developed using data mining technique. There are differences according to gender, age, type of insurance, type of admission, but there is no difference of whether patients died in hospital. After yielding the standardized value of the difference between crude and expected length of stay, we analysed the variation of length of stay for community-acquired pneumonia. There was variation of LOS in regional differences and insurance type, though there was no variation according whether patients receive their care in their residences. The variation of length of stay controlling the case mix or severity of illness can be explained the factors of provider. This supply factors in LOS variations should be more studied for individual practice style or patient management practices and healthcare resources or environment. We expect that the severity-adjustment model using administrative databases should be more adapted in other diseases in practical. Key words : Community-Acquired Pneumonia, Length of stay, Severity-Adjustment, Data mining, Administrative Database

Changes and determinants affecting on geographic variations in health behavior, prevalence of hypertension and diabetes in Korean

요 약 본 연구의 목적은 지역의 건강행태, 고혈압, 당뇨병 유병률의 변화와 변화율의 지역 간 변이에 영향을 미치 는 요인을 분석하는 것이다. 이를 위해 2008년과 2013년 지역사회건강조사 결과를 이용하였으며, 5년간 지역 간 건 강행태 변화와 고혈압 및 당뇨병 유병률 변화의 지역 간 변이 정도, 변이의 요인을 확인하기 위해 지리정보시스템, 의사결정나무 등 융복합적 분석을 하였다. 지난 5년간 현재 흡연율과 월간 음주율의 증가는 남서부 지역에서 높았고, 걷기 실천율의 증가는 서부 지역에서 다소 높게 나타났다. 고혈압은 서부와 남부, 당뇨병은 동부와 북부 지역에서 증가율이 높았다. 고혈압 및 당뇨병 유병률 변화의 지역 간 변이 요인은 고혈압 및 당뇨병 이외에 음주, 신체활동, 비만, 관절염, 우울증상 및 스트레스로 나타났다. 우울증상이 증가하는 지역에서 고혈압과 당뇨병의 유병률의 증가는 중요한 영향을 미치는 것으로 나타났다. 따라서 고혈압과 당뇨병의 유병률을 감소시키기 위해서는 지역특성에 기반 한 주민 정신건강 관리 프로그램을 개발할 필요가 있다.

Comparison of Hospital Standardized Mortality Ratio Using National Hospital Discharge Injury Data

This study was to develop the assessment of medical service outcome using administration data through compared with hospital standardized mortality ratios(HSMR) in various hospitals. This study analyzed 63,664 cases of Hospital Discharge Injury Data of 2007 and 2008, provided by Korea Centers for Disease Control and Prevention. We used data mining technique and compared decision tree and logistic regression for developing risk-adjustment model of in-hospital mortality. Our Analysis shows that gender, length of stay, Elixhauser comorbidity index, hospitalization path, and primary diagnosis are main variables which influence mortality ratio. By comparing hospital standardized mortality ratios(HSMR) with standardized variables, we found concrete differences (55.6-201.6) of hospital standardized mortality ratios(HSMR) among hospitals. This proves that there are quality-gaps of medical service among hospitals. This study outcome should be utilized more to achieve the improvement of the quality of medical service.

A study on the variation of severity adjusted LOS on Injry inpatient in Korea

In order to analyze the variation in length of stay(LOS) of injury inpatients, we developed severity-adjusted LOS model using Korean National Discharge In-depth Injury Survey data of Center for Disease Control. Appling this model, we calculated predicted values and, after standardizing LOS using the differences from the actual values, analyzed the variation in LOS. Major factors affecting severity-adjusted LOS of injury inpatients were found to be severity, surgery(or no surgery), age, injury mechanism and channel of hospitalization. Result of analysis of the differences between the actual values and predicted values adjusted by decision tree model suggested that there were statistically significant differences by hospital size(number of beds), type of insurance and location of institution. In order to reduce the variation in LOS, efforts should be exerted in developing nationwide treatment protocol, inducing medical institutions to utilize it, and furthermore systematically evaluating it to reduce the variation continually.

A Study on the Efficient Flow of Health Examinees

The purpose of this study is to optimize the patient(examinee) flow in a health examination center via a simulation model and to improve operational efficiency. Two experimentation scenarios were implemented into the simulation model to determine which proposed scenario provides better improvement in terms of the following performance measures: LOS(Length of Stay), staff utilization, and occupancy level. The simulation results demonstrated that there was no significant difference in response results of two scenarios. Although the original motivation of this study was suggest optimal policy for a patient(examinee) flow, the insight into applying simulation in efficiently managing hospital operations is of more value. Simulation approach is a powerful technique that supports efficient decision-making compared to traditional healthcare management approach based on past experience, feelings, and intuition. Therefore, the proposed experimentation model has wide applicability in healthcare systems.

Severity-Adjusted LOS Model of AMI patients based on the Korean National Hospital Discharge in-depth Injury Survey Data

This study aims to design a Severity-Adjusted LOS(Length of Stay) Model in order to efficiently manage LOS of AMI(Acute Myocardial Infarction) patients. We designed a Severity-Adjusted LOS Model with using data-mining methods(multiple regression analysis, decision trees, and neural network) which covered 6,074 AMI patients who showed the diagnosis of I21 from 2004-2009 Korean National Hospital Discharge in-depth Injury Survey. A decision tree model was chosen for the final model that produced superior results. This study discovered that the execution of CABG, status at discharge(alive or dead), comorbidity index, etc. were major factors affecting a Sevirity-Adjustment of LOS of AMI patients. The difference between real LOS and adjusted LOS resulted from hospital location and bed size. The efficient management of LOS of AMI patients requires that we need to perform various activities after identifying differentiating factors. These factors can be specified by applying each hospital`s data into this newly designed Severity-Adjusted LOS Model.

Group Classification on Management Behavior of Diabetic Mellitus

The purpose of this study is to provide informative statistics which can be used for effective Diabetes Management Programs. We collected and analyzed the data of 666 diabetic people who had participated in Korean National Health and Nutrition Examination Survey in 2007 and 2008. Group classification on management behavior of Diabetic Mellitus is based on the K-means clustering method. The Decision Tree method and Multiple Regression Analysis were used to study factors of the management behavior of Diabetic Mellitus. Diabetic people were largely classified into three categories: Health Behavior Program Group, Focused Management Program Group, and Complication Test Program Group. First, Health Behavior Program Group means that even though drug therapy and complication test are being well performed, people should still need to improve their health behavior such as exercising regularly and avoid drinking and smoking. Second, Focused Management Program Group means that they show an uncooperative attitude about treatment and complication test and also take a passive action to improve their health behavior. Third, Complication Test Program Group means that they take a positive attitude about treatment and improving their health behavior but they pay no attention to complication test to detect acute and chronic disease early. The main factor for group classification was to prove whether they have hyperlipidemia or not. This varied widely with an individuals gender, income, age, occupation, and self rated health. To improve the rate of diabetic management, specialized diabetic management programs should be applied depending on each groups character.

A Study on Factors of Management of Diabetes Mellitus using Data Mining

The Objectives: The purpose of this study is to identify the factors related to management of DM in Korea. Methods: The subjects selected by using data of National Health and Nutrition Survey(NHANS) in 2005 were 415 adults, aged 20 and older, and diagnosed with DM. This study used data mining algorithms. This study validated the predictive power of data mining algorithms by comparing the performance of logistic regression, decision tree, and Neural Network on the basic of validation, it was found that the model performance of decision tree was the best among the above three techniques. Result: First, awareness of DM was positively associated with age, residential area, and job. The most important factor of DM awareness is age. Awareness rate of DM with 52 age over is 76.1%. Among the ≥52 age group, an important factor is family history. Among patients who are 52 years or over with family history of DM, an important factor is job. The awareness rate of patients who are 52 age over, family, history of DM, and professionals is 95.0%. Second, treatment of DM was also positively associated with awareness, region, and job. The most important factor of DM treatment is DM awareness. Treatment rate of patients who are aware of DM is 84.8%. Among patients who have awareness of DM, an important factor is region. The awareness rate of patients who are aware of DM in rural area is 10.4%. Conclusion: Finally, the result of analysis suggest that DM management programs should consider group characteristic of DM patients.