• Journal of Preventive Medicine and Public Health
• /
• v.25 no.1 s.37
• /
• pp.53-63
• /
• 1992

There are increasing interest and need for information on health care consumer with the significance of hospital marketing and strategic planning being increasingly emphasized. This study was conducted to investigate the criteria for selection of medical facilities according to the characteristics of health care consumer by the types of medical services on a sample of 1,500 population aged 20 years and above. Major findings are as follows ; 1. When considering the criteria for selection of medical facilities into two factors, namely, quality or convenience factors, convenience factor was the major contributor for outpatient and dental services whereas it was quality factor for inpatient services. 2. Females and those residing in large cities selected medical facilities based on convenience factor in the outpatient services. In the case of inpatient service, persons who considered their present health status to be good and whose ages were 50 years old and above choose medical facilities based on quality factor. 3. Persons who considered medical facilities to be profit-making tended to choose medical facilities based on convenience factor for outpatient services. There were no differences in the cases of inpatient and dental services. 4. There was no significant difference on the criteria for selection of medical facilities according to the decision maker for selection or trust on medical facilities. On the use of health service information, selection of medical facilities was based on quality factor for those who made more use of the information in the cases of outpatient and dental services. 5. Analysis using the logistic regression model on the criteria for the selection of medical facilities with the characteristics of health care consumer as independent variables was performed. The selection of medical facilities was significantly related with residential area, sex, and use of information on medical facilities for outpatient services and with age, average monthly income, and perception of health status for inpatient services. For dental services significant association with residential area and use of information on medical facilities was seen. The results of this study, despite some limitations, can be used as baseline data for marketing and strategic planning of hospital management.

• Korean Journal of Health Education and Promotion
• /
• v.26 no.2
• /
• pp.75-86
• /
• 2009

Objectives: To identify the factors associated with the intention to undergo mammography among Korean women without a prior screening experience. Methods: Among 1,039 women of the general population, we selected 145 women (mean age: 54.2 years, age range : 40-78 years) without any prior experience with mammography. They were recruited for the 'Cancer Information Needs Assessment Survey' by using the method of random multi-stage cluster sampling. Data on the socio-demographic characteristics, intention to undergo mammography based on the Precaution Adoption Process Model, level of self belief and self efficacy for breast cancer screening, motivation for decision to undergo breast cancer screening were obtained by conducting a household survey. Results: Of the study subjects, 49.7% were classified as "unengaged" and "decided not to act" regarding breast cancer screening. Women with the intention to undergo mammography were more likely to be younger (OR 0.11, 95%CI 0.04-0.36), to have been recommended to undergo screening by others (OR 3.27, 95%CI 1.36-7.87), to have a high level of perceived sensitivity (OR 3.15, 95%CI 1.27-7.82), and to have a high level of self efficacy (OR 1.09, 95%CI 0.97-1.23). Exposure to campaigns and information regarding breast cancer screening, whether cancer patients are or not in around, perceived severity, perceived benefit, and perceived cost were factors that were not significantly associated with the intention to undergo mammography. Conclusion: It is necessary to develop tailored intervention strategies for women who have never undergone breast cancer screening on the basis of their demographic characteristics and factors that positively influence the intention to undergo mammography.

• Journal of Preventive Medicine and Public Health
• /
• v.34 no.4
• /
• pp.337-346
• /
• 2001

Objective : To determine the clinical risk factors associated with the mode of delivery decision and to compare cesarean section rates after adjusting for risk factors identified among Korean hospitals. Methods Data were collected from 9 general hospitals in two provincial regions by medical record abstraction during February 2000. A total of 3,467 cases were enrolled and analyzed by stepwise logistic regression. Performance of the risk-adjustment model (discrimination and calibration) was evaluated by the C statistic and the Hosmer-Lemeshow test. Crude rates, predicted rates with 95% confidence intervals, and adjusted rates of cesarean section were calculated and compared among the hospitals. Results : The average crude cesarean section rate was 53.2%, ranging from 39.4% to 65.7%. Several risk factors such as maternal age, previous history of cesarean section, placenta previa, placental abruption, malpresentation, amniotic fluid abnormality, gestational anemia, infant body weight, pregnancy-induced hypertension, and chorioamnionitis were found to have statistically significant effects on the mode of delivery. It was confirmed that information about most of these risk factors was able to be collected through the national health insurance claims database in Korea. Performance of the risk-adjustment model was good (c statistic=0.815, Hosmer-Lemeshow test=0.0621). Risk factor adjustment did lead to some change in the rank of hospital cesarean section rates. The crude rates of three hospitals were beyond 95% confidence intervals of the predicted rates. Conclusions : Considering that cesarean section rates in Korean hospitals are too high, it is apparent that some policy interventions need to be introduced. The concept and methodology of risk adjustment should be used in the process of health policy development to lower the cesarean section rate in Korea.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.35 no.11
• /
• pp.155-162
• /
• 2019

The construction industry is the highest safety accident causing industry as 28.55% portion of all industries' accidents in Korea. In particular, falling is the highest accidents type composed of 60.16% among the construction field accidents. Therefore, we analyzed the factors of major disaster affecting the fall accident and then derived feature importances by considering various variables. We used data collected from Korea Occupational Safety & Health Agency (KOSHA) for learning and predicting in the proposed model. We have an effort to predict the degree of occupational fall accidents by using the machine learning model, i.e., Adaboost, short for Adaptive Boosting. Adaboost is a machine learning meta-algorithm which can be used in conjunction with many other types of learning algorithms to improve performance. Decision trees were combined with AdaBoost in this model to predict and classify the degree of occupational fall accidents. HyOperpt was also used to optimize hyperparameters and to combine k-fold cross validation by hierarchy. We extracted and analyzed feature importances and affecting fall disaster by permutation technique. In this study, we verified the degree of fall accidents with predictive accuracy. The machine learning model was also confirmed to be applicable to the safety accident analysis in construction site. In the future, if the safety accident data is accumulated automatically in the network system using IoT(Internet of things) technology in real time in the construction site, it will be possible to analyze the factors and types of accidents according to the site conditions from the real time data.

• PNF and Movement
• /
• v.14 no.3
• /
• pp.157-176
• /
• 2016

Purpose: The purpose of this study was to share an experience about processes and lessons learned to execute evidence-based practice (EBP) in neurological physical therapy. Methods: The most important thing in applying EBP to practice is to search, find, and appraise the existing evidence. Many evidence databases are available, such as CENTRAL, PEDro, PUBMED, and EMBASE. However, the knowledge represented in these databases is not always perfect. The practice model is a set of processes to resolve client problems. Therapists should make hypothesis-focused decisions through EBP. Integrating clinical reasoning and evidence is most important when it comes to the execution of EBP. Results: The process of EBP consisted of following: coming up with clinical questions, followed by searching for, appraising, evaluating, and integrating evidence. To integrate EBP into practice, it is necessary to consider clinical expertise, patient value and preferences, as well as research wth the best evidence. We provided an example of a clinical case with a stroke patient to show how this process and framework concerning clinical reasoning through evidences can be integrateds. During this process, we also utilized information technology to improve EBP ability. Conclusion: We should recognize what manner of information is needed to resolve eash patient's problem, and we should search for this information efficiently. Then, we should judge the value of the information obtained as it applies, to the clinical setting.

• Health Policy and Management
• /
• v.15 no.2
• /
• pp.16-36
• /
• 2005

Due to the existence of asymmetry of information between doctor and patient, it has been believed that doctor might affect patient's decision making process of purchasing medical care. Based on this notion, doctor's reimbursement method has been suggested as an effective policy device of improving efficiency of patient's medical care use by way of its affecting doctor's practice pattern. By using the Community Tracking Study (CTS) household and physician data set, which includes not only various information on patient's medical care use, but doctor's practice arrangements and sources of practice revenue, this paper investigates the effect of community doctor's characteristics of reimbursement method on community patient's medical care use under the control of patient's socio-demographic characteristics and community doctor's practice type. In the process of estimating econometric model, the endogeneity problem of individual health insurance purchase was corrected by using 2818. And due to the existence of sample selection problem, Heckman's two-step estimation method was used for strengthen the robustness of estimation which was adversely affected by sample selection problem The empirical results show that as the average value of community doctor's portion of practice revenue determined by prospective method out of total revenue increases, the community patient's total out-of-pocket medical cost decreases. This results suggest, as doctor's practice revenues are mainly determined by prospective method, such as capitation, doctors would be more conscious about practice cost, which might affect doctor's practice pattern and by which his/her patient's use of medical care would decrease.

• Smart Structures and Systems
• /
• v.31 no.3
• /
• pp.247-257
• /
• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• Journal of health informatics and statistics
• /
• v.42 no.4
• /
• pp.309-316
• /
• 2017

Objectives: Radon and its progeny pose environmental risks as a carcinogen, especially to the lungs. Investigating factors affecting indoor radon concentrations and models thereof are needed to prevent exposure to radon and to reduce indoor radon concentrations. The purpose of this study was to identify factors affecting indoor radon concentration and to construct a comprehensive model thereof. Methods: Questionnaires were administered to obtain data on residential environments, including building materials and life style. Decision tree and structural equation modeling were applied to predict residences at risk for higher radon concentrations and to develop the comprehensive model. Results: Greenery ratio, impermeable layer ratio, residence at ground level, daily ventilation, long-term heating, crack around the measuring device, and bedroom were significantly shown to be predictive factors of higher indoor radon concentrations. Daily ventilation reduced the probability of homes having indoor radon concentrations ${\geq}200Bq/m^3$ by 11.6%. Meanwhile, a greenery ratio ${\geq}65%$ without daily ventilation increased this probability by 15.3% compared to daily ventilation. The constructed model indicated greenery ratio and ventilation rate directly affecting indoor radon concentrations. Conclusions: Our model highlights the combined influences of geographical properties, groundwater, and lifestyle factors of an individual resident on indoor radon concentrations in Korea.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.3
• /
• pp.1437-1443
• /
• 2016

Background: We investigated four factors, height, weight gain since age 20, physical activity, and alcohol drinking, for associations with risk of breast cancer (BC) according to menopausal status, using the latest data of the Japan Collaborative Cohort Study (JACC Study). Materials and Methods: We confined the analysis to 24 areas available of cancer incidence information, excluding women with a previous diagnosis of BC. Baseline data were collected from 38,610 (9,367 premenopausal, and 29,243 postmenopausal) women during 1988 and 1990. The study subjects were followed-up at the end of 2009, and 273 (84 premenopausal, and 189 postmenopausal) cases of BC were newly diagnosed in 501,907 person-years. The Cox model was used to estimate a hazards ratio (HR) and its 95% confidence interval (CI) of BC risk. Results: As a result of the multivariate analysis adjusting for age at baseline survey, age at menarche, number of live births, and, age at first delivery, weight gain since age 20 of 6.7 kg-9.9 kg, and ${\geq}10.0kg$ were significantly associated with increased risk for postmenopausal BC (HR=2.48, 95% CI 1.40-4.41, and, HR=2.94, 95% CI 1.84-4.70, respectively). Significantly increased trend of BC risk was also observed in weight gain since age 20 (p for trend, p<0.001). Amount of ethanol intake per day${\geq}15.0g$ was significantly associated with increased risk for postmenopausal BC in the multivariable-adjusted analysis (HR=2.74, 95% CI 1.32-5.70). Conclusions: Higher weight gain in adulthood and larger amounts of ethanol intake were significantly associated with increased risk of BC in Japanese postmenopausal women. None of the investigated factors were significantly associated with BC risk in Japanese premenopausal women.

• Journal of Preventive Medicine and Public Health
• /
• v.29 no.4 s.55
• /
• pp.831-842
• /
• 1996

Demand for high quality medical care has recently been increasing in step with high level of income and education. Patients prefer the use of large general hospitals to small community hospitals. Large hospitals, usually located at urban area, expand their capacities to cope with the increasing demand, therefore, they easily secure revenue necessary for growth and development of hospitals. However, small community hospitals are facing with serious financial difficulties caused from the reduction of patients in one hand and the inflation of cost in another. If small rural hospitals were closed, the closure would have negative impacts on local economies in addition to the decrease in access to medical care. Community leaders should have an insight on the contribution of community hospitals to local economies. They could make a rational decision on the hospital closure only with the understanding of hospital's contribution to the community. This study is designed to develop an economic model to estimate the contribution of rural hospital to local economies, and also to apply this model with a specific hospital. The contribution of a hospital to local economies consists of two elements, direct effect and multiplier effects. The direct impacts include hospital's local purchasing power, employee's local purchasing power, and the consumption of patients coming from outside the community. The direct impact induces multiplication effect in the local economy. The seed money invested to other industries grows through economic activities in the region. This study estimated the direct effect with the data of expenditure of the case hospital. The total effect was calculated by multiplied the direct effect with a multiplier. The multiplier was drown from the ratio of marginal propensity of income and expenditure. Beside the estimation of the total impacts, the economic effect from the external resources was also analyzed by the use of the ratio of patients coming outside the region. The results are as follows. 1. The direct economic contribution of the hospital to the local economy is 1,104 million won. 2. The value of multiplier in the region is 2.976. 3. The total economic effect is 3,286 million won, and the multiplication effect is 2,182 million won. 4. The economic contribution from the external resources is 245 million won which is 7.5% of the total economic effect.